-
Declaring Values and Variables:
- declare a constant:
val answer = 8*5
- declare a variable whose contents can vary:
var counter = 0
- specify the type if necessary:
val greeting: String = null
- multiple values:
val xmax, ymax = 100
- declare a constant:
-
Types:
-
Byte, Char, Short, Int, Long, Float, Double, Boolean
-
examples:
1.toString() // "1" 1.to(10) // Range(1,2,3,4,5,6,7,8,9,10) "Hello".intersect("world") // "lo"
-
-
Arithmetic and Operator Overloading: Operators are actually methods.
a + b // a.+(b) 1 to 10 // 1.to(10) 10 to 1// empty range counter+=1 // no ++
-
More about Calling Methods:
"Bonjour".sorted // "Bjnooru", without()
import scala.math._ // _ as * in Java
sqrt(2)
scala.math.sqrt(2) // if don't import scala.math package
-
The apply Method:
val s = "Hello" s(4) // yields 'o', equals to s.apply(4) ("Bonjour".sorted)(3) "Bonjour".sorted.apply(3)
-
Other tips:
-
Scala allows you to define operators, leaving it up to you to use this feature with restraint and good taste.
-
"crazy" * 3 // "crazycrazycrazy" 10 max 2 // 10
-
In Scala, an if/else has a value, namely the value of the expression that follows the if or else.
if (x > 0) 1 else -1 // either 1 or -1
val s = if (x > 0) 1 else -1 // can be assigned to a value
if(x > 0) s = 1 else s = -1 // same as the last row
// The first form is better because it can be used to initialize a val. The second form needs s to be a var.
// no a?: operation in scala
In Scala, every expression has a type.
if (x > 0) 1 else -1 // Int type
if (x > 0) "positive" else -1 // mixed-type: java.lang.String and Int
if (x > 0) 1
if (x > 0) 1 else ()
In scala, a semicolon is never required if it falls just before the end of the line. However, if you want to have more than one statement on a single line, you need to separate them with semicolons.
if (n > 0) { r = r * n; n -= 1 }
If you want to continue a long statement over two lines, make sure that the first line ends in a symbol that cannot be the end of a statement. An operator is often a good choice.
s = s0 + (v - v0) * t + // The + tells the parser that this is not the end
0.5 * (a - a0) * t * t
if (n > 0) {
r = r * n
n -= 1
}
We can also use the semicolons, they do no harm.
In Scala, a { } block contains a sequence of expressions, and the result is also an expression. The value of the block is the value of the last expression.
val distance = { val dx = x - x0; val dy = y - y0; sqrt(dx * dx + dy * dy) }
An assignment has no value, or, strictly speaking, they have a value of type Unit. Recall that the Unit type is the equivalent of the void type in Java and C++, with a single value written as ().
{ r = r * n; n -= 1 } // has a unit value, be aware of it when defining functions
x = y = 1 // No
To print a value, use the print
or println
function. The latter adds a newline character after the printout.
print("Answer: ")
println(42)
// is same as
println("Answer: " + 42)
//or
printf("Hello, %s! You are %d years old.%n", name, age)
print(f"Hello, $name! In six months, you'll be ${age + 0.5}%7.2f years old.%n")
// A formatted string is prefixed with the letter f, it is better than printf because it's type-safe
To input, use scala.io.StdIn
.
import scala.io
val name = StdIn.readLine("Your name: ")
print("Your age: ")
val age = StdIn.readInt()
println(s"Hello, ${name}! Next year, you will be ${age + 1}.")
While
loops like Java and C++.
while (n > 0) {
r = r * n
n -= 1
}
for loops:
val s = "Hello"
var sum = 0
for (i <- 0 to s.length - 1)
sum += s(i)
// or
for (ch <- "Hello") sum += ch
- In Scala, loops are not used as often as in other languages. As you will see in Chapter 12, you can often process the values in a sequence by applying a function to all of them, which can be done with a single method call.
- In Scala, there is no
break
orcontinue
. We can use a Boolean variable, a nested functions to return from the middle of a function or usebreak
method inscala.util.control.Breaks._
Advanced for Loops
for (i <- 1 to 3; j <- 1 to 3) print(f"${10 * i + j}%3d") // 11 12 13 21 22 23 31 32 33
for (i <- 1 to 3; j <- 1 to 3 if i != j) print(f"${10 * i + j}%3d") // 12 13 21 23 31 32
for (i <- 1 to 3; from = 4 - i; j <- from to 3) print(f"${10 * i + j}%3d")
// 13 22 23 31 32 33
for (i <- 1 to 10) yield i % 3 // Vector(1, 2, 0, 1, 2, 0, 1, 2, 0, 1)
Scala has functions in addition to methods. A method operates on an object, but a function doesn’t. C++ has functions as well, but in Java, you have to imitate them with static methods.
The Scala compiler determines the return type from the type of the expression to the right of the = symbol.
- A very simple absolute value function:
def abs(x: Double) = if (x >= 0) x else -x
- Function with more than one expression
def fac(n: Int) = {
var r = 1
for (i <- 1 to n) r = r * i
r
} // The last expression of the block becomes the value that the function returns
-
A recursive function must have the return type specified.
def fac(n: Int): Int = if (n<=0) 1 else n * fac(n - 1)
The named arguments should come first.
def decorate(str: String, left: String = "[", right: String = "]") =
left + str + right
decorate("Hello") // "[Hello]"
decorate("Hello", "<<<", ">>>") "<<<Hello>>>"
decorate(left = "<<<", str = "Hello", right = ">>>") // need not to be in the same order.
Example of variable arguments:
def sum(args: Int*) = {
var result = 0
for (arg <- args) result += arg
result
}
val s = sum(1, 4, 9, 16, 25)
val s = sum(1 to 5) // not correct, cannot pass a range
def recursiveSum(args: Int*) : Int = {
if (args.length == 0) 0
else args.head + recursiveSum(args.tail : _*)
}
val s = sum(1 to 5: _*) // consider 1 to 5 as an argument sequence
Scala has a special notation for a function that returns no value. If the function body is enclosed in braces without a preceding = symbol, then the return type is Unit. Such a function is called a procedure. A procedure returns no value, and you only call it for its side effect.
def box(s : String) { // Look carefully: no =
val border = "-" * (s.length + 2)
print(f"$border%n|$s|%n$border%n")
}
// omit the '=' or use "Unit"
def box(s : String): Unit = {
...
}
-------
|Hello|
-------
When a val is declared as lazy, its initialization is deferred until it is accessed for the first time.
lazy val words = scala.io.Source.fromFile("/usr/share/dict/words").mkString
If we never accesses words
, then the file is never opened.
Lazy values are useful to delay costly initialization statements. They can also deal with other initialization issues, such as circular dependencies. Moreover, they are essential for developing lazy data structures
Scala exceptions work the same way as in Java or C++. When you throw an exception, for example:
throw new IllegalArgumentException("x should not be negative")
However, unlike Java, Scala has no “checked” exceptions—you never have to declare that a function or method might throw an exception.
...skip for now.
-
def signum(n: Int): Int = {if (n > 0) 1 else if (n < 0) -1 else 0}
-
for (i <- 10.to(0,-1)) println(i)
An array whose length does not change, use Array
type in Scala.
val nums = new Array[Int](10) // An array of ten integers, all initialized with zero
val a = new Array[String](10) // A string array with ten elements, initialized with null
// When we supply initial values, we don't need to specify the type, because the type can be inferred, and we also don't use 'new'
val s = Array("Hello","World")
s(0) = "Goodbye" // Use () to access the elements
An array whose length can change, use ArrayBuffer
type in Scala.
import scala.collection.mutable.ArrayBuffer
val b = ArrayBuffer[Int]() // An empty array buffer
val b = new ArrayBuffer[Int] // An empty array buffer
b += 1 // Add an element at the end by +=
b += (1, 2, 3, 5) // Add multiple elements at the end by += (...)
b ++= Array(8, 13, 21) // Append any collection with ++= operator
b.trimEnd(5) // Remove the last five elements, efficient
// Insert and remove at an arbitrary location is not efficient
b.insert(2, 6) // Insert 6 before index 2
b.insert(2, 7, 8, 9) // Insert 7,8,9 before index 2
b.remove(2) // Remove the element at index 2
b.remove(2, 3) // Remove 3 elements starting from index 2
// The conversion between Array and ArrayBuffer:
b.toArray
a.toBuffer
To traverse an array or array buffer with a for
loop:
for (i <- 0 until a.length)
println(s"$i: ${a(i)}")
// The 'until' method is similar to the 'to' method, except that it excludes the last value.
for (i <- 0 to a.length - 1)
println(s"$i: ${a(i)}")
// Others
for (i <- 0 until a.length by 2) // Range(0, 2, 4, ...)
println(s"$i: ${a(i)}")
for (i <- 0 until a.length by -1) // Range(..., 2, 1, 0)
println(s"$i: ${a(i)}")
// If we don't the index, we can directly tranverse a
for (elem <- a)
println(elem)
// Instead of 'until' we can use:
a.indices
a.indices.reverse
In Scala, it is easy to take an array (or array buffer) and transform it in some way. Such transformations don’t modify the original array but yield a new one. Use the for/yield
loop.
val a = Array(2, 3, 5, 7, 11)
val result1 = for (elem <- a) yield 2 * elem // Resulting in an Array(4, 6, 10, 14, 22)
val result2 = for (elem <- a if elem % 2 == 0) yield 2 * elem
// Or
a.filter(_ % 2 == 0).map(2 * _)
a filter {_ % 2 == 0} map {2 * _}
Generally, it is better to have all index values together instead of seeing them one by one.
val result = for (elem <- a if elem >= 0) yield elem // This way to find all non-negative elements, rather than using while loop and find them one by one
// We can keep the positions to remove
val positionsToRemove = for (i <- a.indices if a(i) < 0) yield i
for (i <- positionsToRemove.reverse) a.remove(i)
// Or
val positionsToKeep = for (i <- a.indices if a(i) >= 0) yield i
for (j <- positionsToKeep.indices) a(j) = a(positionsToKeep(j))
a.trimEnd(a.length - positionsToKeep.length)
Scala has built-in functions for sums and sortings. In order to use the sum method, the element type must be a numeric type: either an integral or floating-point type or BigInteger/BigDecimal.
import scala.collection.mutable.ArrayBuffer
Array(1, 7, 2, 9).sum // 19, works for ArrayBuffer too
ArrayBuffer("Mary", "had", "a", "little", "lamb").max // "little"
val b = ArrayBuffer(1, 7, 2, 9)
val bSorted = b.sorted // b is unchanged, bSorted is ArrayBuffer(1,2,7,9)
// Sort an array but not array buffer in place
val a = Array(1, 7, 2, 9)
scala.util.Sorting.quickSort(a) // a is now Array(1, 2, 7, 9)
We can display the contents of an array or array buffer:
a.mkString(" and ") // "1 and 2 and 7 and 9"
a.mkString("<", ",", ">") //"<1,2,7,9>"
b.toString
// "ArrayBuffer(1, 7, 2, 9)"
// The toString method reports the type, which is useful for debugging
Check the book...
Like in Java, multidimensional arrays are implemented as arrays of arrays. For example, a two-dimensional array of Double
values has the type Array[Array[Double]]. To construct such an array, use the ofDim
method:
val matrix = Array.ofDim[Double](3, 4) // Three rows, four columns
matrix(row)(column) = 42 // To access an element
// We can make ragged arrays, with varying row lengths
val triangle = new Array[Array[Int]](10)
triangle(i) = new Array[Int](i + 1)
Since Scala arrays are implemented as Java arrays, you can pass them back and forth between Java and Scala.
-
// import scala.util.Random def rand(n: Int) = new Array[Int](n).map(_ => Random.nextInt(n))
A classic programmer’s saying is, “If you can only have one data structure, make it a hash table.” Hash tables—or, more generally, maps—are among the most versatile data structures.
Maps are collections of key/value pairs. Scala has a general notion of tuples— aggregates of n objects, not necessarily of the same type. A pair is simply a tuple with n = 2. Tuples are useful whenever you need to aggregate two or more values together.
By default, you get a hash map, but you can also get a tree map. Tuples are useful for aggregating values.
// constructs an immutable Map[String, Int] whose contents cannot be changed.
val scores = Map("Alice" -> 10, "Bob" -> 3, "Cindy" -> 8)
// constructs a mutable map
val scores = scala.collection.mutable.Map("Alice" -> 10, "Bob" -> 3, "Cindy" -> 8)
// we have to specify the type parameters if we want to build a empty map
val scores = scala.collection.mutable.Map[String, Int]()
val bobsScore = scores("Bob")
If the map doesn’t contain a value for the requested key, an exception is thrown. To check whether there is a key with the given value, call the contains
method:
val bobsScore = if (scores.contains("Bob")) scores("Bob") else 0
// if the map contains the key "Bob", return the value; otherwise, return 0
val bobsScore = scores.getOrElse("Bob", 0)
In a mutable map, you can update a map value, or add a new one, with a () to the left of an = sign:
// update rule of mutable map
scores("Bob") = 10 // update the existing value for a key
scores("Fred") = 7 // add new key/value pair
scores += ("Bob" -> 10, "Fred" -> 7) // add a series of pairs
scores -= "Alice" //remove a pair
// we cannot update an immutable map, but we can do this:
val newScores = scores + ("Bob" -> 10, "Fred" -> 7)
// or
var scores = ...
scores = scores + ("Bob" -> 10, "Fred" -> 7)
scores += ("Bob" -> 10, "Fred" -> 7) // we can use this update rule if scores is a var
// remove a key from an immutable map
scores = scores - "Alice"
// or
scores -= "Alice" // same as a mutable map
for ((k, v) <- scores) {do your things}
for (v <- scores.values) println(v)
scores.keySet // A set such as Set("Bob", "Cindy", "Fred", "Alice")
// reverse a map
for ((k, v) <- map) yield (v, k)
There are two common implementation strategies for maps: hash tables and balanced trees. Hash tables use the hash codes of the keys to scramble entries, so iterating over the elements yields them in unpredictable order
. By default, Scala gives you a map based on a hash table because it is usually more efficient. If you need to visit the keys in sorted order, use a SortedMap
instead.
val scores = scala.collection.mutable.SortedMap("Alice" -> 10,
"Fred" -> 7, "Bob" -> 3, "Cindy" -> 8)
If you want to visit the keys in insertion order, use a LinkedHashMap
. For example,
val months = scala.collection.mutable.LinkedHashMap("January" -> 1,
"February" -> 2, "March" -> 3, "April" -> 4, "May" -> 5, ...)
Check the book...
Maps are collections of key/value pairs. Pairs are the simplest case of tuples— aggregates of values of different types. A tuple value is formed by enclosing individual values in parentheses.
val t = (1, 3.14, "Fred") // a tuple of type Tuple3[Int, Double, Java.lang.String]
val second = t._2 // access its compoments with the methods _1, _2, _3
// or
val second = t _2
// note that the component positions of a tuple start with 1, not 0.
// pattern matching
val (first, second, third) = t // Sets first to 1, second to 3.14, third to "Fred"
val symbols = Array("<", "-", ">")
val counts = Array(2, 10, 2)
val pairs = symbols.zip(counts)
// yields an array of pairs Array(("<", 2), ("-", 10), (">", 2))
// the pairs can then be processed together
for ((s, n) <- pairs) print(s * n) // Prints <<---------->>
// we can use toMap method turns a collection pairs into a map
keys.zip(values).toMap // a Map
-
val discount = for((k, v) <- gizmos ) yield (k,v * 0.9)
-
def minmax(a: Array[Int]) = (a.min, a.max)
-
def lteqgt(values: Array[Int], v: Int) = (values.count(_<v), values.count(_==v), values.count(_>v))
In Scala, a class is not declared as public. A Scala source file can contain multiple classes, and all of them have public visibility.
// a class example
class Counter {
private var value = 0 // You must initialize the field
def increment() { value += 1 } // Methods are public by default
def current() = value
}
// to use this class
val myCounter = new Counter()
myCounter.increment()
println(myCounter.current) // do not change the state, so we drop the parentheses
// we can call parameterless method without parentheses
// we can define parameterless method without parentheses
It is considered good style to use () for a mutator method (a method that changes the object state), and to drop the () for an accessor method (a method that does not change the object state).
With a public field, anyone could write to the parameter and change it. That’s why we prefer to use getter and setter methods:
public class Person { // This is Java
private int age;
public int getAge() { return age; }
public void setAge(int age) { this.age = age; }
}
Getters and setters are better than public fields because they let you start with simple get/set semantics and evolve them as needed.
Scala provides getter and setter methods for every field. Here, we define a public field:
class Person {
var age = 0
}
Scala generates a class for the JVM with a private age
field and getter
and setter
methods. These methods are public because we did not declare age as private. (For a private field, the getter and setter methods are private.)
In Scala, the getter and setter methods are called age and age_=. For example,
println(fred.age) // calls the method fred.age()
fred.age = 21 // calls fred.age_ = (21)
Sometimes you want a read-only property with a getter but no setter. If the value of the property never changes after the object has been constructed, use a val
field.
Sometimes, however, you want a property that a client can’t set at will, but that is mutated in some other way. You can’t implement such a property with a val—a val never changes. Instead, provide a private field and a property getter, like this:
class Counter {
private var value = 0
def increment() { value += 1}
def current = value // No () in declaration
}
// Note that there are no () in the definition of the getter method. Therefore, you
// must call the method without parentheses:
val n = myCounter.current // Calling myCounter.current() is a syntax error
To summarize, you have four choices for implementing properties:
var foo
: Scala synthesizes a getter and a setter.val foo
: Scala synthesizes a getter.- You define methods
foo
andfoo_=
. - You define a method
foo
.
In Scala (as well as in Java or C++), a method can access the private fields of all objects of its class. For example,
class Counter {
private var value = 0
def increment() { value += 1 }
def isLess(other : Counter) = value < other.value
// Can access private field of other object
}
Scala allows an even more severe access restriction with the private[this]
qualifier:
private[this] var value = 0
Now, the methods of the Counter class can only access the value field of the current object, not of other objects of type Counter. This access is sometimes called object-private
.
With a class-private field, Scala generates private getter and setter methods. However, for an object-private field, no getters and setters are generated at all.
Check the book...
a Scala class can have as many constructors as you like. However, a Scala class has one constructor that is more important than all the others, called the primary constructor
. In addition, a class may have any number of auxiliary constructors
.
- The auxiliary constructors are called this. (In Java or C++, constructors have the same name as the class—which is not so convenient if you rename the class.)
- Each auxiliary constructor must start with a call to a previously defined auxiliary constructor or the primary constructor.
class Person {
private var name = ""
private var age = 0
def this(name: String) { // An auxiliary constructor
this() // Calls primary constructor
this.name = name
}
def this(name: String, age: Int) { // Another auxiliary constructor
this(name) // Calls previous auxiliary constructor
this.age = age
}
}
// construct the objects in three ways
val p1 = new Person // Primary constructor
val p2 = new Person("Fred") // First auxiliary constructor
val p3 = new Person("Fred", 42) // Second auxiliary constructor
In Scala, every class has a primary constructor. The primary constructor is not defined with a this
method. Instead, it is interwoven with the class definition.
-
The parameters of the primary constructor are placed immediately after the class name.
class Person(val name: String, val age: Int) { // Parameters of primary constructor in (...) ... }
-
The primary constructor executes all statements in the class definition. For example, in the following class, e.g.,
class Person(val name: String, val age: Int) { println("Just constructed another person") // a part of the primary constructor def description = s"$name is $age years old" }
-
You can often eliminate auxiliary constructors by using default arguments in the primary constructor. For example:
class Person(val name: String = "", val age: Int = 0)
If you find the primary constructor notation confusing, you don’t need to use it. Just provide one or more auxiliary constructors in the usual way, but remember to call this() if you don’t chain to another auxiliary constructor.
In Scala, you can nest just about anything inside anything. You can define functions inside other functions, and classes inside other classes. Here is a simple example of the latter:
import scala.collection.mutable.ArrayBuffer
class Network {
class Member(val name: String) {
val contacts = new ArrayBuffer[Member]
}
private val members = new ArrayBuffer[Member]
def join(name: String) = {
val m = new Member(name)
members += m
m
}
}
val chatter = new Network
val myFace = new Network
In Scala, each instance has its own class Member, just like each instance has its own field members. That is, chatter.Member and myFace. Member are different classes. In our network example, you can add a member within its own network, but not across networks.
In this short chapter, you will learn when to use the object construct in Scala. Use ptg20087099 it when you need a class with a single instance, or when you want to find a home for miscellaneous values or functions.
Scala has no static methods or fields. Instead, you use the object
construct. An object defines a single instance of a class with the features that you want.
// When you need a new unique account number in your application, call Accounts.newUniqueNumber().
object Accounts {
private var lastNumber = 0
def newUniqueNumber() = { lastNumber += 1; lastNumber}
}
The constructor of an object is executed when the object is first used. In our example, the Accounts constructor is executed with the first call to Accounts. newUniqueNumber()
. If an object is never used, its constructor is not executed.
Use an object in Scala whenever you would have used a singleton object in Java or C++:
- As a home for utility functions or constants
- When a single immutable instance can be shared efficiently
- When a single instance is required to coordinate some service (the singleton design pattern)
In Java or C++, you often have a class with both instance methods and static methods. In Scala, you can achieve this by having a class and a “companion” object of the same name.
class Account {
val id = Account.newUniqueNumber()
private var balance = 0.0
def deposit(amount: Double) { balance += amount }
}
object Account { // The companion object
private var lastNumber = 0
private def newUniqueNumber() = { lastNumber += 1; lastNumber}
}
The class and its companion object can access each other’s private features. They must be located in the same source file
.
Note that the companion object’s features are not in the scope of the class. The result is an object of a class that extends the given class and/or traits, and in addition has all of the features specified in the object definition.
An object can extend a class and/or one or more traits. The result is an object of a class that extends the given class and/or traits, and in addition has all of the features specified in the object definition.
object DoNothingAction extends UndoableAction("Do nothing") {
override def undo() {}
override def redo() {}
}
It is common to have objects with an apply method. The apply method is called for expressions of the form: Object(arg1, ..., argN)
. Typically, such an apply method returns an object of the companion class.
class Account private (val id: Int, initialBalance: Double) {
private var balance = initialBalance
...
}
object Account {
def apply(initialBalance: Double) =
new Account(newUniqueNumber(), initialBalance)
...
}
// Now you can construct an account as
val acct = Account(1000.0)
Each Scala program must start with an object’s main
method of type Array[String] => Unit
:
object Hello {
def main(args: Array[String]) {
println("Hello, World!")
}
}
Instead of providing a main
method for your application, you can extend the App
trait and place the program code into the constructor body:
object Hello extends App {
println("Hello, world!")
}
If you need the command-line arguments, you can get them from the args property:
object Hello extends App {
if (args.length > 0)
println(f"Hello ${args(0)}")
else
println("Hello, World!")
}
Unlike Java or C++, Scala does not have enumerated types. However, the standard library provides an Enumeration
helper class that you can use to produce enumerations. Define an object that extends the Enumeration
class and initialize each value in your enumeration with a call to the Value
method. For example,
object TrafficLightColor extends Enumeration {
val Red, Yellow, Green = Value
}
Each call to the Value method returns a new instance of an inner class, also called Value.
Alternatively, you can pass IDs, names, or both to the Value method:
val Red = Value(0, "Stop")
val Yellow = Value(10)
val Green = Value("Go")
You can now refer to the enumeration values as TrafficLightColor.Red, TrafficLightColor.Yellow, and so on. If that gets too tedious, use
import TrafficLightColor._
The call TrafficLightColor.values
yields a set of all values:
for (c <- TrafficLightColor.values) println(s"${c.id}: $c")
Some people recommend that you add a type alias:
object TrafficLightColor extends Enumeration {
type TrafficLightColor = Value
val Red, Yellow, Green = Value
}
Now the type of the enumeration is TrafficLightColor.TrafficLightColor, which is only an improvement if you use an import statement. For example,
import TrafficLightColor._
def doWhat(color: TrafficLightColor) = {
if (color == Red) "stop"
else if (color == Yellow) "hurry up"
else "go"
}
Finally, you can look up an enumeration value by its ID or name. Both of the following yield the object TrafficLightColor.Red:
TrafficLightColor(0) // Calls Enumeration.apply
TrafficLightColor.withName("Red")
To add items to a package, you can include them in package statements, such as:
package com {
package horstmann {
package impatient {
class Employee
...
}
}
}
Then the class name Employee can be accessed anywhere as com.horstmann. impatient.Employee
.
Unlike an object or a class, a package can be defined in multiple files. The preceding code might be in a file Employee.scala, and a file Manager.scala might contain
package com {
package horstmann {
package impatient {
class Employee
...
}
}
}
Conversely, you can contribute to more than one package in a single file. The file Employee.scala
may contain:
package com {
package horstmann {
package impatient {
class Employee
...
}
}
}
package net {
package bigjava {
class Counter
...
}
}
There is no enforced relationship between the directory of the source file and the package
.You don’t have to put Employee.scala
and Manager.scala
into a com/horstmann/impatient
directory.
Scala packages nest just like all other scopes. You can access names from the enclosing scope. For example,
package com {
package horstmann {
object Utils {
def percentOf(value: Double, rate: Double) = vlaue * rate / 100
...
}
package impatient {
class Employee {
...
def giveRaise(rate: scala.Double) {
salary += Utils.percentOf(salary, rate) //**
}
}
}
}
}
The following code takes advantage of the fact that the scala package is always imported. Therefore, the collection package is actually scala.collection
.
package com {
package horstmann {
package impatient {
class Manager {
val subordinates = new collection.mutable.ArrayBuffer[Employee]
...
}
}
}
}
A package clause can contain a “chain,” or path segment, such a clause limits the visible members. Now a com.horstmann.collection
package would no longer be accessible as collection
.
package com.horstmann.impatient {
// Members of com and com.horstmann are not visible here
package people {
class Person
...
}
}
we can also change the aforementioned codes as:
package com.horstmann.impatient
package people
class Person
...
A package can contain classes, objects, and traits, but not the definitions of functions or variables. That’s an unfortunate limitation of the Java virtual machine. It would make more sense to add utility functions or constants to a package than to some Utils
object. Package objects address this limitation.
Every package can have one package object. You define it in the parent package, and it has the same name as the child package. For example,
package com.horstmann.impatient
package object people {
val defaultName = "John Q. Public"
}
package people {
class Person {
var name = defaultName // A constant from the package
}
...
}
The following method is visible in its own package:
package com.horstmann.impatient.people
class Person {
private[people] def description = s"A person with name $name"
...
}
// you can extend the visibility to an enclosing package:
private[impatient] def description = s"A person with name $name"
Imports let you use short names instead of long ones. With the clause
import java.awt.Color
you can write Color in your code instead of java.awt.Color.
import java.awt._ // to import all members of a package as
You can also import all members of a class or object.
import java.awt.Color._
val c1 = RED // Color.RED
val c2 = decode("#ff0000") // Color.decode
Once you import a package, you can access its subpackages with shorter names.
import java.awt._
def handler(evt: event.ActionEvent) { // java.awt.event.ActionEvent
...
}
In Scala, an import statement can be anywhere, not just at the top of a file. The scope of the import statement extends until the end of the enclosing block. For example,
class Manager {
import scala.collection.mutable._
val subordinates = new ArrayBuffer[Employee]
...
}
By putting the imports where they are needed, you can greatly reduce the potential for conflicts.
If you want to import more than one member from a package, use a selector like this:
import java.awt.{Color, Font}
// The selector syntax lets you rename members:
import java.util.{HashMap => JavaHashMap}
import scala.collection.mutable._
Now JavaHashMap is a java.util.HashMap and plain HashMap is a scala.collection.mutable. HashMap.
The selector HashMap => _ hides a member instead of renaming it. This is only useful if you import others:
import java.util.{HashMap => _, _}
import scala.collection.mutable._
Now HashMap unambiguously refers to scala.collection.mutable.HashMap since java.util. HashMap is hidden.
Every Scala program implicitly starts with
import java.lang._
import scala._
import Predef._
As with Java programs, java.lang is always imported. Next, the scala package is imported, but in a special way. Unlike all other imports, this one is allowed to override the preceding import. For example, scala.StringBuilder overrides java.lang.StringBuilder instead of conflicting with it.
Finally, the Predef object is imported. It contains commonly used types, implicit conversions, and utility methods. (The methods could equally well have been placed into the scala package object, but Predef was introduced before Scala had package objects.)
// we do not need to write package names that start with scala. E.g.,
collection.mutable.HashMap
// is equal to
scala.collection.mutable.HashMap
Highlights in this chapter:
- The
extends
andfinal
keywords are as in Java - You must use
override
when you override a method - Only the primary constructor can call the primary superclass constructor
- You can override fields
Like in Java,
class Employee extends Person {
var salary = 0.0
...
}
we can specify fields and methods that are new to the subclass or that override the methods in the superclass.
You can declare a class final
so that it cannot be extended. You can also declare individual methods or fields final
so that they cannot be overridden.
In Scala, you must use the override
modifier when you override a method that isn’t abstract.
class Person {
...
override def toString = s"${getClass.getName}[name=$name]"
}
Invoking a superclass method in Scala works exactly like in Java, with the keyword super
:
class Employee extends Person {
...
override def toString = s"${super.getName}[name=$name]"
}
The call super.toString invokes the toString method of the superclass—that is, the Person.toString method.
To test whether an object belongs to a given class, use the isInstanceOf
method. . If the test succeeds, you can use the asInstanceOf method to convert a reference to a subclass reference:
if (p.isInstanceOf[Employee]) {
val s = p.asInstanceOf[Employee] // s has type Employee
...
}
The p.isInstanceOf[Employee]
test succeeds if p refers to an object of class Employee
or its subclass (such as Manager
).
If p is null
, then p.isInstanceOf[Employee]
returns false and p.asInstanceOf[Employee]
returns null
.
If p is not an Employee, then p.asInstanceOf[Employee]
throws an exception.
If you want to test whether p refers to an Employee object, but not a subclass, use
if (p.getClass == classOf[Employee])
As in Java or C++, you can declare a field or method as protected
. Such a member is accessible from any subclass, but not from other locations.
Recall from Chapter 5 that a class has one primary constructor and any number of auxiliary constructors, and that all auxiliary constructors must start with a call to a preceding auxiliary constructor or the primary constructor.
As a consequence, an auxiliary constructor can never invoke a superclass constructor directly. Because the auxiliary constructors of the subclass eventually call the primary constructor of the subclass, and only the primary constructor can call a superclass constructor.
Intertwining the class and the constructor makes for very concise code. You may find it helpful to think of the primary constructor parameters as parameters of the class. Here, the Employee class has three parameters: name, age, and salary, two of which it “passes” to the superclass.
class Employee(name: String, age: Int, val salary : Double) extends Person(name, age)
corresponding Java version is
public class Employee extends Person {
private double salary;
public Employee(String name, int age, double salary) {
super(name, age)
this.salary = salary
}
}
In a Scala constructor, you can never call super(params), as you would in Java, to call the superclass constructor.
Recall from Chapter 5 that a field in Scala consists of a private field and accessor/mutator methods. You can override a val
(or a parameterless def
) with another val field of the same name.
abstract class Person {
def id: Int // Each person has an ID that is computed in some way
...
}
class Student(override val id: Int) extends Person
// A student ID is simply provided in the constructor
- A def can only override another def.
- A val can only override another val or a parameterless def.
- A var can only override an abstract var.
As in Java, you make an instance of an anonymous subclass if you include a block with definitions or overrides, such as
val alien = new Person("Fred") {
def greeting = "Greetings, Earthling! My name is Fred."
}
Technically, this creates an object of a structural type. The type is denoted as Person{def greeting: String}. You can use this type as a parameter type:
def meet(p: Person{def greeting: String}) {
println(s"${p.name} says: ${p.greeting}")
}
As in Java, you can use the abstract keyword to denote a class that cannot be instantiated, usually because one or more of its methods are not defined. For example,
abstract class Person(val name: String) {
def id: Int // No method body, this is an abstract method
}
Here we say that every person has an ID, but we don’t know how to compute it. Each concrete subclass of Person needs to specify an id method. In Scala, unlike Java, you do not use the abstract keyword for an abstract method. You simply omit its body. As in Java, a class with at least one abstract method must be declared abstract.
In a subclass, you need not use the override
keyword when you define a method that was abstract in the superclass.
class Employee(name: String) extends Person(name) {
def id = name.hashCode // override keyword not required
}
In addition to abstract methods, a class can also have abstract fields. An abstract field is simply a field without an initial value.
abstract class Person {
val id: Int
var name: String
}
This class defines abstract getter methods for the id and name fields, and an abstract setter for the name field. The generated Java class has no fields.
Concrete subclasses must provide concrete fields,
class Employee(val id: Int) extends Person {
var name = ""
}
As with methods, no override keyword is required in the subclass when you define a field that was abstract in the superclass.
You can always customize an abstract field by using an anonymous type:
val fred = new Person {
val id = 1729
var name = "Fred"
}
Check the book...
-
The classes that correspond to the primitive types in Java, as well as the type Unit, extend
AnyVal
. -
You can also define your own
value classes
. -
All other classes are subclasses of the
AnyRef
class. -
Both
AnyVal
andAnyRef
extend theAny
class, the root of the hierarchy. -
The
Any
class defines methodsisInstanceOf
,asInstanceOf
, and the methods for equality and hash codes. -
AnyVal
does not add any methods. It is just a marker for value types. -
The AnyRef class adds the monitor methods wait and notify/notifyAll from the Object class. It also provides a synchronized method with a function parameter.
-
All Scala classes implement the marker interface ScalaObject, which has no methods.
Picture on page101...
The ???
method is declared with return type Nothing. It never returns but instead throws a NotImplementedError when invoked. You can use it for methods that you still need to implement:
class Person(val name: String) {
def description = ???
}
In Scala, the eq method of the AnyRef class checks whether two references refer to the same object. The equals method in AnyRef calls eq. When you implement a class, you should consider overriding the equals method to provide a natural notion of equality for your situation.
if you define a class Item(val description: String, val price: Double)
, you might want to consider two items equal if they have the same description and price. Here is an appropriate equals method:
final override def equals(other: Any) = {
other.isInstanceOf[Item] && {
val that = other.asInstanceOf[Item]
description == that.description && price == that.price
}
}
// or better, use pattern matching:
final override def equals(other: Any) = other match {
case that: Item => description == that.description && price == that.price
case _ => false
}
When you define equals, remember to define hashCode as well. The hash code should be computed only from the fields that you use in the equality check, so that equal objects have the same hash code. In the Item example, combine the hash codes of the fields.
final override def hashCode = (description, price).##
The ##
method is a null-safe version of the hashCode method that yields 0 for null instead of throwing an exception.
In an application program, you don’t generally call eq or equals. Simply use the == operator. For reference types, it calls equals after doing the appropriate check for null operands.
Some classes have a single field, such as the wrapper classes for primitive types, and the “rich” or “ops” wrappers that Scala uses to add methods to existing types. It is inefficient to allocate a new object that holds just one value. Value classes allow you to define classes that are “inlined,” so that the single field is used directly.
A value class has these properties:
- The class extends AnyVal. 2. Its primary constructor has exactly one parameter, which is a val, and no body. 3. The class has no other fields or constructors. 4. The automatically provided equals and hashCode methods compare and hash the underlying value.
// define a value class that wraps a “military time” value:
class MilTime(val time: Int) extends AnyVal {
def minutes = time % 100
def hours = time / 100
override def toString = f"$time04d"
}
To read all lines from a file, call the getLines
method on a scala.io.Source
object.
import scala.io.Source
val source = Source.fromFile("myfile.txt", "UTF-8")
val lineIterator = source.getLines // result in an iterator
for (l <- lineIterator) process l
Or you can put the lines into an array or array buffer by applying the toArray or toBuffer method to the iterator:
val lines = source.getLines.toArray
// Sometimes, you just want to read an entire file into a string.
val contents = source.mkString
Call close when you are done using the Source object.
To read individual characters from a file, you can use a Source object directly as an iterator since the Source
class extends Iterator[Char]
:
for (c <- source) process c
if your file isn’t large, you can just read it into a string and process that:
val contents = source.mkString
Here is a quick-and-dirty way of reading all whitespace-separated tokens in a source:
val tokens = source.mkString.split("\\s+")
To convert a string into a number, use the toInt or toDouble method. For example, if you have a file containing floating-point numbers, you can read them all into an array by
val numbers = for (w <- tokens) yield w.toDouble
// or
val number = tokens.map(_.toDouble)
Finally, note that you can read numbers from scala.io.StdIn:
print("How old are you?")
val age = Scala.io.readInt() // or use readDouble or readLong
The Source object has methods to read from sources other than files:
val source1 = Source.fromURL("http://horstmann.com", "UTF-8")
val source2 = Source.fromString("Hello, World!")
// Reads from the given string—useful for debugging
val source3 = Source.stdin
// Reads from standard input
Scala has no provision for reading binary files. You’ll need to use the Java library. Here is how you can read a file into a byte array:
val file = new File(filename)
val in = new FileInputStream(file)
val bytes = new Array[Byte](file.length.toInt)
in.read(bytes)
in.close()
Scala has no built-in support for writing files. To write a text file, use a java.io.PrintWriter, for example:
val out = new PrintWriter("numbers.txt")
for (i <- 1 to 100) out.println(i)
out.close()
Check the book...
Here is how you declare a serializable class in Java and Scala.
//Java:
public class Person implements java.io.Serializable {
private static final long serialVersionUID = 42L;
...
}
//Scala:
@SerialVersionUID(42L) class Person extends Serializable
Check the book...
When you process input, you often want to use regular expressions to analyze it. The scala.util.matching.Regex
class makes this simple. To construct a Regex object, use the r method of the String class:
val numPattern = "[0-9]+".r
// If the regular expression contains backslashes or quotation marks, then it is a
// good idea to use the “raw” string syntax, """...""".
val wsnumwsPattern = """\s+[0-9]+\s+""".r
The findAllIn
method returns an Iterator[String]
through all matches. You can use it in a for loop:
for (matchString <- numPattern.findAllIn("99 bottles, 98 bottles"))
println(matchString)
// Alternatively, turn the iterator into an array:
val matches = numPattern.findAllIn("99 bottles, 98 bottles").toArray
// To find the first match in a string, use findFirstIn.
val firstMatch = wsnumwsPattern.findFirstIn("99 bottles, 98 bottles")
Groups are useful to get subexpressions of regular expressions. Add parentheses around the subexpressions that you want to extract,
val numitemPattern = "([0-9]+)([a-z]+)".r
This chapter covers in detail implementing your own operators—methods with ptg20087099 the same syntax as the familiar mathematical operators. Operators are often used to build domain-specific languages—minilanguages embedded inside Scala.
The names of variables, functions, classes, and so on are collectively called identifiers
. As in Java, Unicode characters are allowed.
We can also use:
-
The ASCII characters ! # % & * + - / : < = > ? @ \ ^ | ~ that are not letters, digits, underscore, the .,; punctuation marks, parentheses () [] {}, or quotation marks ' ` ".
-
Unicode mathematical symbols or other symbols from the Unicode categories Sm and So. For example, ** and \sqrt are valid identifiers.
-
Finally, you can include just about any sequence of characters in backquotes. For example,
val `val` = 42
We can writea identifier b
where identifier denotes a method with two parameters (one implicit, one explicit). For example, the expression
1 to 10
// is actually a method call
1.to(10)
This is called an infix(中缀) expression because the operator is between the arguments. The operator can contain letters, as in to, or it can contain operator characters—for example,
1 -> 10
// is actually a method call
1.->(10)
To define an operator in your own class, simply define a method whose name is that of the desired operator. For example, here is a Fraction class that multiplies two fractions according to the law
// (n1 / d1) × (n2 / d2) = (n1n2 / d1d2)
class Fraction(n: Int, d: Int) {
private val num = ...
private val den = ...
...
def *(other:Fraction) = new Fraction(num * other.num, den * other.den)
}
Infix operators are binary operators—they have two parameters. An operator with one parameter is called a unary operator.
-
The four operators
+, -, !, ~
are allowed as prefix operators, appearing before their arguments. They are converted into calls to methods with the name unary_operator. For example,-a
means the same asa.unary_-
. -
If a unary operator follows its argument, it is a postfix operator. The expression
a identifier
is the same as the method calla.identifier()
. For example,42 toString // is the same as 42.toString()
An assignment operator has the form operator=
, and the expression a operator= b
means the same as a = a operator b
.
- <=, >=, and != are not assignment operators.
- An operator starting with an = is never an assignment operator (==, ===, =/=, and so on).
- If a has a method called operator=, then that method is called directly.
Scala can have arbitrary operators, so it uses a scheme that works for all operators, while also giving the familiar precedence order to the standard ones.
Except for assignment operators, the precedence is determined by the first character of the operator.
in the same row yield operators with the same precedence. For example, +
and ->
have the same precedence.
Postfix operators have lower precedence than infix operators:
a infixOp bpostfixOp
is the same as(a infixOp b)postfixOp
When you have a sequence of operators of the same precedence, the associativity determines whether they are evaluated left-to-right or right-to-left. For example, in the expression 17 – 2 – 9, one computes (17 – 2) – 9. The – operator is left-associative.
In Scala, all operators are left-associative except for
- operators that end in a colon (:)
- assignment operators
In particular, the ::
operator for constructing lists is right-associative. For example, 1 :: 2 :: Nil
means 1 :: (2 :: Nil)
.
val a = List(1, 2, 3)
val b = List(4, 5, 6)
a::b // List(List(1, 2, 3), 4, 5, 6)
a++b // List(1, 2, 3, 4, 5, 6)
A right-associative binary operator is a method of its second argument. For example, 2 :: Nil
means Nil.::(2)
- Scala lets you extend the function call syntax
f(arg1, arg2, ...)
to values other than functions. If f is not a function or method, then this expression is equivalent to the callf.apply(arg1, arg2, ...)
. - When it occurs to the left of an assignment. The expression
f(arg1, arg2, ...) = value
corresponds to the callf.update(arg1, arg2, ..., value)
This mechanism is used in arrays and maps. For example,
val scores = new scala.collection.mutable.HashMap[String, Int]
scores("Bob") = 100
val bobScore = scores("Bob")
The apply method is also commonly used in companion objects to construct objects without calling new. For example, consider a Fraction class.
class Fraction(n: Int, d:Int) {
...
}
object Fraction {
def apply(n: Int, d: Int) = new Fraction(n, d)
}
Because of the apply method, we can construct a fraction as Fraction(3, 4)
instead of new Fraction(3, 4)
. That sounds like a small thing, but if you have many Fraction values, it is a welcome improvement: val result = Fraction(3, 4) * Fraction(2, 5)
An extractor is an object with an unapply method. You can think of the unapply method as the opposite of the apply method of a companion object. An apply
method takes construction parameters and turns them into an object. An unapply
method takes an object and extracts values from it—usually the values from which the object was constructed.
Consider the Fraction class from the preceding section. The apply method makes a fraction from a numerator and denominator. An unapply method retrieves the numerator and denominator. You can use it in a variable definition
var Fraction(a, b) = Fraction(3, 4) * Fraction(2, 5)
// a, b are initialized with the numerator and denominator of the result
or a pattern match
case Fraction(a,b) => ... // a, b are bound to the numerator and denominator
A declaration val Fraction(a, b) = f
becomes
val tupleOption = Fraction.unapply(f)
if (tupleOption == None) throw new MatchError
// tupleOption is Some((t1, t2))
val a = t1
val b = t2
In the preceding example, the apply and unapply methods are inverses of one another. However, that is not a requirement. You can use extractors to extract information from an object of any type.
In Scala, there are no tuples with one component. If the unapply method extracts a single value, it should just return an Option of the target type. For example,
object Number {
def unapply(input: String): Option[Int] =
try {
Some(input.trim.toInt)
} catch {
case ex: NumberFormatException => None
}
}
With this extractor, you can extract a number from a string: val Number(n) = "1729"
Check the book...
Check the book...
Scala mixes object orientation with functional features. In a functional programming language, functions are first-class citizens that can be passed around and manipulated just like any other data types. This is very useful whenever you want to pass some action detail to an algorithm. In a functional language, you just wrap that detail into a function that you pass as a parameter.
In Scala, a function is a first-class citizen, just like a number. You can store a function in a variable:
import scala.math._
val num = 3.14
val fun = ceil _
// this code sets num to 3.14 and fun to the ceil function
The _
behind the ceil function indicates that you really meant the function, and you didn’t just forget to supply the arguments.
Technically, the _ turns the ceil method into a function. In Scala, you cannot manipulate methods, only functions
Here is how to call the function stored in fun: fun(num) // 4.0
As you can see, the normal function call syntax is used. The only difference is that fun is a variable containing a function, not a fixed function.
Here is how you can give fun
to another function:
Array(3.14, 1.42, 2.0).map(fun) // Array(4.0, 2.0, 2.0)
The map method accepts a function, applies it to all values in an array, and returns an array with the function values.
In Scala, you don’t have to give a name to each function, just like you don’t have to give a name to each number.
(x: Double) => 3 * x
// Of course, we can store this function in a variable
val triple = (x: Double) => 3 * x
// this is the same as
def triple(x: Double) = 3 * x
// but we don't need to name it
Array(3.14, 1.42, 2.0).map((x: Double) => 3 * x)
// or
Array(3.14, 1.42, 2.0) map {(x: Double) => 3 * x }
In this section, you will see how to implement a function that takes another function as a parameter.
def valueAtOneQuarter(f: (Double) => Double) = f(0.25)
// parameter can be any function receiving and returning a Double
// Another example
valueAtOneQuarter(ceil _)
valueAtOneQuarter(sqrt _)
// The type of valueAtOneQuarter is ((Double) => Double) => Double
Since valueAtOneQuarter is a function that receives a function, it is called a higher-order function.
A higher-order function can also produce a function.
def mulBy(factor: Double) = (x: Double) => factor * x
For example, mulBy(3) returns the function (x : Double) => 3 * x which you have seen in the preceding section. The power of mulBy
is that it can deliver functions that multiply by any amount
When you pass an anonymous function to another function or method, Scala helps you out by deducing types when possible. For example, you don’t have to write
valueAtOneQuarter((x: Double) => 3 * x) // 0.75
// because it has the type ((Double) => Double) => Double
def valueAtOneQuarter(f: (Double) => Double) = f(0.25)
Since the valueAtOneQuarter method knows that you will pass in a (Double) => Double function, you can just write
valueAtOneQuarter((x) => 3 * x)
As a special bonus, for a function that has just one parameter, you can omit the () around the parameter:
// we can further write it as
valueAtOneQuarter(x => 3 * x)
If a parameter occurs only once on the right-hand side of the =>, you can replace it with an underscore:
// Finally
valueAtOneQuarter(3 * _)
Keep in mind that these shortcuts only work when the parameter types are known.
val fun = 3 * _ // Error: Can't infer types
val fun = 3 * (_: Double) // OK
val fum: (Double) => Double = 3 * _
You have seen map
, which applies a function to all elements of a collection and returns the result. Here is a quick way of producing a collection containing 0.1, 0.2, . . . , 0.9:
(1 to 9).map(0.1 * _)
Another example,
(1 to 9).map("*" * _).foreach(println _)
Here, we also use foreach, which is like map except that its function doesn’t return a value. The foreach method simply applies the function to each argument.
The filter method yields all elements that match a particular condition. For example, here’s how to get only the even numbers in a sequence:
(1 to 9).filter(_ % 2 == 0)
Of course, that’s not the most efficient way of getting this result.
The reduceLeft
method takes a binary
function—that is, a function with two parameters—and applies it to all elements of a sequence, going from left to right. For example,
(1 to 9).reduceLeft(_ * _) // Each underscore denotes a separate parameter.
// (...((1 * 2) * 3) * ... * 9)
You also need a binary function for sorting. For example,
"Mary had a little lamb".split(" ").sortWith(_.length < _.length)
In Scala, you can define a function inside any scope: in a package, in a class, or even inside another function or method. In the body of a function, you can access any variables from an enclosing scope. That may not sound so remarkable, but note that your function may be called when the variable is no longer in scope.
Such a function is called a closure. A closure consists of code together with the definitions of any nonlocal variables that the code uses.
These functions are actually implemented as objects of a class, with an instance variable factor and an apply method that contains the body of the function.
In Scala, you pass a function as a parameter whenever you want to tell another function what action to carry out.
Confused about this section...
Currying (named after logician Haskell Brooks Curry) is the process of turning a function that takes two arguments into a function that takes one argument. That function returns a function that consumes the second argument.
// a function takes two arguments
val mul = (x: Int, y: Int) => x * y
// a function takes one arguments
val mulOneAtATime = (x: Int) => ((y: Int) => x * y)
// to call
mulOneAtATime(6)(7)
mul(6, 7)
// When you use def, there is a shortcut for defining such curried methods in Scala:
def mulOneAtATime(x: Int)(y: Int) = x * y
Sometimes, you can use currying for a method parameter so that the type inferencer has more information. For example,
val a = Array("Hello", "World")
val b = Array("hello", "world")
a.corresponds(b)(_.equalsIgnoreCase(_))
Note that the function _.equalsIgnoreCase(_)
is passed as a curried parameter, in a separate set of (...). When you look into the Scaladoc, you will see that corresponds is declared as
def corresponds[B](that: Seq[B])(p: (A, B) => Boolean): Boolean
The that sequence and the predicate function p are separate curried parameters. The type inferencer can figure out what B is from the type of that, and then it can use that information when analyzing the function that is passed for p.
In Scala, one can model a sequence of statements as a function with no parameters or return value. For example, here is a function that runs some code in a thread:
def runInThread(block: () => Unit) {
new Thread {
override def run () { block() }
}.start()
}
The code is given as a function of type () => Unit. However, when you call this function, you need to supply an unsightly () =>:
runInThread{ () => println("Hi"); Thread.sleep(10000); println("Bye") }
To avoid the () => in the call, use the call by name notation: Omit the (), but not the =>, in the parameter declaration and in the call to the parameter function:
def runInThread(block: => Unit) {
new Thread {
override def run() { block }
}.start()
}
// To call
runInThread { println("Hi"); Thread.sleep(10000); println("Bye") }
we can innovate a bit and define an until statement that works like while, but with an inverted condition:
def until(condition: => Boolean)(block: => Unit) {
if (!condition) {
block
until(condition)(block)
}
}
// To call
var x = 10
until (x == 0) {
x -= 1
println(x)
}
In Scala, you don’t use a return statement to return function values. The return value of a function is simply the value of the function body.
However, you can use return to return a value from an anonymous function to an enclosing named function. This is useful in control abstractions. For example, consider this function:
def indexOf(str: String, ch: Char): Int = {
var i = 0
until (u == str.length) {
if (str(i) == ch) return i
i += 1
}
return -1
}
Here, the anonymous function { if (str(i) == ch) return i; i += 1 } is passed to until. When the return expression is executed, the enclosing named function indexOf terminates and returns the given value.
If you use return inside a named function, you need to specify its return type. For example, in the indexOf function above, the compiler was not able to infer that it returns an Int.
The control flow is achieved with a special exception that is thrown by the return expression in the anonymous function, passed out of the until function, and caught in the indexOf function.
-
def values(fun: (Int) => Int, low: Int, high: Int) = for (i <- low to high) yield (i,fun(i))
-
max_value = a.reduceLeft((x, y) => if (x > y) x else y)
-
def factorial(num: Int) = (1 to num).reduceLeft(_ * _)
-
def largest(fun: (Int) => Int, inputs: Seq[Int]) = inputs.map(fun).reduceLeft((x, y) => if (x > y) x else y)
-
def largest_index(fun: (Int) => Int, inputs: Seq[Int]) = inputs.map(x => (x, fun(x)).reduceLeft((x, y) => if (x._2 > y._2) x else y)._1
Key points:
- All collections extend the
Iterable
trait. - The three major categories of collections are sequences, sets and maps
- Scala has mutable and immutable versions of most collections
- A Scala list is either empty, or it has a head and a tail which is again a list.
- Sets are unordered collections.
- + adds an element to an unordered collection; +: and :+ prepend or append to a sequence; ++ concatenates two collections; - and -- remove elements.
- Use a
LinkedHashSet
to retain the insertion order or aSortedSet
to iterate in sorted order. - Mapping, folding, and zipping are useful techniques for applying a function or operation to the elements of a collection
An Iterable is any collection that can yield an Iterator with which you can access all elements in the collection:
val coll = ... // some Iterable
val iter = coll.iterator
while (iter.hasNext)
do something with iter.next()
A Seq
is an ordered sequence of values, such as an array or list. An IndexedSeq
allows fast random access through an integer index. For example, an ArrayBuffer
is indexed but a linked list is not.
A Set is an unordered collection of values. In a SortedSet, elements are always visited in sorted order.
A Map is a set of (key, value) pairs. A SortedMap visits the entries as sorted by the keys.
There are methods toSeq, toSet, toMap
, and so on, as well as a generic to[C]
method, that you can use to translate between collection types.
val coll = Seq(1, 1, 2, 3, 5, 8. 13)
val set = coll.toSet
val buffer = coll.to[ArrayBuffer]
Scala supports both mutable and immutable collections. For example, there is a scala.collection.mutable.Map
and a scala.collection.immutable.Map
. Both have a common supertype scala.collection.Map (which, of course, contains no mutation operations).
Moreover, the scala
package and the Predef
object, which are always imported, have type aliases List, Set, and Map
that refer to the immutable traits. For example, Predef.Map
is the same as scala.collection.immutable.Map
.
A Vector
is the immutable equivalent of an ArrayBuffer
: an indexed sequence with fast random access. Vectors are implemented as trees where each node has up to 32 children. For a vector with one million elements, one needs four layers of nodes. Accessing an element in such a list will take 4 hops, whereas in a linked list it would take an average of 500,000.
A Range
represents an integer sequence, such as 0,1,2,3,4,5,6,7,8,9 or 10,20,30. Of course a Range object doesn’t store all sequence values but only the start, end, and increment. You construct Range objects with the to
and until
methods.
In Scala, a list is either Nil (that is, empty) or an object with a head element and a tail that is again a list.
val digits = List(4,2)
The value of digits.head
is 4, and digits.tail
is List(2). Moreover, digits.tail.head
is 2 and digits.tail.tail
is Nil
.
The :: operator makes a new list from a given head and tail. For example,
9 :: List(4,2) // List(9, 4, 2)
// also
9 :: 4 :: 2 :: Nil
// Note that :: is right-associative. With the :: operator, lists are constructed from
// the end:
9 :: (4 :: (2 :: Nil))
In Java or C++, one uses an iterator to traverse a linked list. You can do this in Scala as well, but it is often more natural to use recursion. For example, the following function computes the sum of all elements in a linked list of integers:
def sum(lst: List[Int]): Int =
if (lst == Nil) 0 else lst.head + sum(lst.tail)
// or use pattern matching
def sum(lst: List[Int]): Int = lst match {
case Nil => 0
case h :: t => h + sum(t) // h is lst.head, t is lst.tail
}
// Note the :: operator in the second pattern. It “destructures” the list into head
// and tail.
// we can directly use the library
List(9,4,2).sum
If you want to mutate list elements in place, you can use a ListBuffer, a data structure that is backed by a linked list with a reference to the last node. This makes it efficient to add or remove elements at either end of the list.
However, adding or removing elements in the middle is not efficient. Of course, removing multiple elements by their index positions is very inefficient in a linked list. Your best bet is to generate a new list with the result
A set is a collection of distinct elements. Trying to add an existing element has no effect:
Set(2, 0, 1) + 1 // Set(2, 0, 1)
Unlike lists, sets do not retain the order in which elements are inserted. By default, sets are implemented as hash sets in which elements are organized by the value of the hashCode method.
For example, if you iterate over Set(1, 2, 3, 4, 5, 6)
the elements are visited in the order 5 1 6 2 3 4
You may wonder why sets don’t retain the element order. It turns out that you can find elements much faster
if you allow sets to reorder their elements. Finding an element in a hash set is much faster than in an array or list.
A linked hash set remembers the order in which elements were inserted. It keeps a linked list for this purpose.
val weekdays = scala.collection.mutable.LinkedHashSet("MO", "TU", "We", "Th", "Fr")
// if you want to iterate over elements in sorted order, use a sorted set
val numbers = scala.collection.mutable.SortedSet(1, 2, 3, 4, 5)
The contains method checks whether a set contains a given value. The subsetOf method checks whether all elements of a set are contained in another set.
val digits = Set(1, 7, 2, 9)
digits contains 0 // False
Set(1,2) subsetOf digits // True
The union, intersect, and diff
methods carry out the usual set operations. If you prefer, you can write them as |, &, and &~
. You can also write union as ++ and difference as --
.
Generally, +
is used for adding an element to an unordered collection, while +:
and :+
add an element to the beginning or end of an ordered collection.
These operators return new collections (of the same type as the original ones) without modifying the original. Mutable collections have a += operator that mutates the left-hand side.
You may want to transform all elements of a collection. The map method applies a function to a collection and yields a collection of the results.
val names = List("Peter", "Paul", "Mary")
names.map(_.toUpperCase) // List("PETER", "PAUL", "MARY")
// the same as
for (n <- names) yield n.toUpperCase
If the function yields a collection instead of a single value, you may want to concatenate all results. In that case, use flatMap.
def ulcase(s: String) = Vector(s.toUpperCase(), s.toLowerCase())
names.map(ulcase) // List(Vector("PETER", "Peter"), Vector("PAUL", "paul"), Vector("MARY", "mary"))
names.flatMap(ulcase) // List("PETER", "peter", "PAUL", "paul", "MARY", "mary")
Another example,
for (i <- 1 to 10) yield i * i
// is translated to
(1 to 10).map(i => i * i)
for (i <- 1 to 10; j <- 1 to i) yield i * j
// is translated to
(1 to 10).flatMap(i => (1 to i).map(j => i * j))
The transform
method is the in-place equivalent of map. It applies to mutable collections, and replaces each element with the result of a function. For example, the following code changes all buffer elements to uppercase:
val buffer = ArrayBuffer("Peter", "Paul", "Mary")
buffer.transform(_.toUppercase)
If you just want to apply a function for its side effect and don’t care about the function values, use foreach:
names.foreach(println)
Thecollect
method works with partial functions—functions that may not be defined for all inputs. It yields a collection of all function values of the arguments on which it is defined. For example,
"-3+4".collect { case '+' => 1; case '-' => 1 } // Vector(-1, 1)
The groupBy
method yields a map whose keys are the function values, and whose values are the collections of elements whose function value is the given key. For example,
val words = ...
val map = words.groupBy(_.substring(0, 1).toUpper)
builds a map that maps "A" to all words starting with A, and so on.
The map
method applies a unary function to all elements of a collection. The methods that we discuss in this section combine elements with a binary function. The call c.reduceLeft(op)
applies op to successive elements.
op(op(coll(0), coll(1)), coll(2))...
List(1, 7, 2, 9).reduceLeft(_ - _)
// (((1-7)-2)-9) = -17
List(1, 7, 2, 9).reduceRight(_ - _)
// 1-(7-(2-9)) = -13
Often, it is useful to start the computation with an initial element other than the initial element of a collection. The call coll.foldLeft(init)(op) computes
op(op(init, coll(0)), coll(1))...
List(1, 7, 2, 9).foldLeft(0)(_ - _)
0 - 1 - 7 - 2 - 9 = -19
The initial value and the operator are separate “curried” parameters so that Scala can use the type of the initial value for type inference in the operator. For example, in List(1, 7, 2, 9).foldLeft("")(_ + _), the initial value is a string, so the operator must be a function (String, Int) => String.
You can also write the foldLeft operation with the /:
operator, like this: (0 /: List(1, 7, 2, 9))(_ - _)
The /: is supposed to remind you of the shape of the tree.
There is a foldRight
or :\
variant as well.
Folding is sometimes attractive as a replacement for a loop. Suppose, for example, we want to count the frequencies of the letters in a string. One way is to visit each letter and update a mutable map.
val freq = scala.collection.mutable.Map[Char, Int]()
for (c <- "Mississippi") freq(c) = freq.getOrElse(c, 0) + 1
// Now freq is Map('i' -> 4, 'M' -> 1, 's' -> 4, 'p' -> 2)
Here is another way of thinking about this process. At each step, combine the frequency map and the newly encountered letter, yielding a new frequency map.
(Map[Char, Int]() /: "Mississippi") {
(m, c) => m + (c -> (m.getOrElse(c, 0) + 1))
}
Finally, the scanLeft and scanRight methods combine folding and mapping. You get a collection of all intermediate results:
(1 to 10).scanLeft(0)(_ + _)
// Vector(0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55)
Sometimes, you have two collections, and you want to combine corresponding elements.
val prices = List(5.0, 20.0, 9.95)
val quantities = List(10,2,1)
prices zip quantities // List[(Double, Int)] = List((5.0, 10), (20.0, 2), (9.95, 1))
// Now it is easy to apply a function to each pair.
(prices zip quantities) map { p => p._1 * p._2 }
// List(50.0, 40.0, 9.95)
// To compute the total price
((prices zip quantities) map { p=> p._1 * p._2 }) sum
If one collection is shorter than the other, the result has as many pairs as the shorter collection.
The zipAll method lets you specify defaults for the shorter list:
List(5.0, 20.0, 9.95).zipAll(List(10, 2), 0.0, 1)
// List((5.0, 10), (20.0, 2), (9.95, 1))
The zipWithIndex method returns a list of pairs where the second component is the index of each element
"Scala".zipWithIndex
// Vector(('S', 0), ('c', 1), ('a', 2), ('l', 3), ('a', 4))
You can obtain an iterator from a collection with the iterator method. This isn’t as common as in Java or C++ because you can usually get what you need more easily with one of the methods from the preceding sections.
However, iterators are useful for collections that are expensive to construct fully. For example, Source.fromFile yields an iterator because it might not be efficient to read an entire file into memory. There are a few Iterable methods that yield an iterator, such as grouped or sliding.
When you have an iterator, you can iterate over the elements with the next and hasNext methods.
while (iter.hasNext)
do something with iter.next()
for (elem <- iter)
do something with elem
Sometimes, you want to be able to look at the next element before deciding whether to consume it. In that case, use the buffered method to turn an Iterator into a BufferedIterator. The head method yields the next element without advancing the iterator.
val iter = scala.io.Source.fromFile(filename).buffered
while (iter.hasNext && iter.head.isWhitespece) iter.next
// Now iter points to the first non-whitespace character
After calling a method such as map, filter, count, sum, or even length, the iterator is at the end of the collection, and you can’t use it again. With other methods, such as find or take, the iterator is past the found element or the taken ones.
In the preceding sections, you saw that an iterator is a “lazy” alternative to a collection.
However, iterators are fragile. Each call to next mutates the iterator. Streams offer an immutable alternative. A stream is an immutable list in which the tail is computed lazily—that is, only when you ask for it.
For example,
def numsFrom(n: BigInt): Stream[BigInt] = n #:: numsFrom(n + 1)
The #::
operator is like the ::
operator for lists, but it constructs a stream.
val tenOrMore = numsFrom(10) // Stream(10, ?)
tenOrMore.tail.tail.tail // Stream(13, ?)
// Stream methods are executed lazily. For example,
val squares = numsFrom(1).map(x => x * x) // Stream(1, ?)
// we have to call squares.tail to force evaluation of the next entry
If you want to get more than one answer, you can invoke take followed by force, which forces evaluation of all values. For example,
squares.take(5).force // Stream(1, 4, 9, 16, 25)
squares.force // No! OutOfMemoryError
You can construct a stream from an iterator. A stream caches the visited lines so you can revisit them
val words = Source.fromFile("/usr/share/dict/words").getLines.toStream
words // Stream(A, ?)
words(5) // Aachen
words // Stream(A, A's, AOL, AOL's, Aachen, ?)
In the preceding section, you saw that stream methods are computed lazily, delivering results only when they are needed. You can get a similar effect with other collections by applying the view
method. This method yields a collection on which methods are applied lazily.
val palindromicSquares = (1 to 1000000).view
.map(x => x * x).filter(x => x.toString == x.toString.reverse)
yields a collection that is unevaluated. (Unlike a stream, not even the first element is evaluated.) When you call
palindromicSquares.take(10).mkString(",")
then enough squares are generated until ten palindromes have been found, and then the computation stops. Unlike streams, views do not cache any values. If you call palindromicSquares.take(10).mkString(",") again, the computation starts over.
- The apply method forces evaluation of the entire view. Instead of calling lazyView(i), call
lazyView.take(i).last
. - As with streams, use the
force
method to force evaluation of a lazy view. You get back a collection of the same type as the original.
When you obtain a view into a slice of a mutable collection, any mutations affect the original collection.
ArrayBuffer buffer = ...
buffer.view(10, 20).transform(x => 0)
// clears the given slice and leaves the other elements unchanged.
Check the book...
Scala offers a particularly attractive solution for manipulating large collections. Such tasks often parallelize naturally. For example, to compute the sum of all elements, multiple threads can concurrently compute the sums of different sections; in the end, these partial results are summed up. Of course it is troublesome to schedule these concurrent activities—but with Scala, you don’t have to. If coll is a large collection, then
coll.par.sum // compute the sum concurrently
The par
method produces a parallel implementation
of the collection. That implementation parallelizes the collection methods whenever possible. For example,
coll.par.count(_ % 2 == 0)
counts the even numbers in coll by evaluating the predicate on subcollections in parallel and combining the results. You can parallelize a for loop by applying .par to the collection over which you iterate, like this:
for (i <- (0 until 100000).par) print(s" $i")
// the numbers are printed in the order they are produced by the threads
// working on the task.
If parallel computations mutate shared variables, the result is unpredictable. For example, do not update a shared counter:
var count = 0
for (c <- coll.par) { if (c % 2 == 0) count += 1} // Error!
The parallel collections returned by the par method belong to types that extend the ParSeq, ParSet, or ParMap traits. These are not subtypes of Seq, Set, or Map, and you cannot pass a parallel collection to a method that expects a sequential collection.
You can convert a parallel collection back to a sequential one with the seq method.
val result = coll.par.filter(p).seq
-
// https://github.com/BasileDuPlessis/scala-for-the-impatient/blob/master/src/main/scala/com/basile/scala/ch13/Ex01.scala import scala.collection.mutable.Map import scala.collection.mutable.SortedSet object Ex1 extends App { def indexes(s: String) = { s.indices.foldLeft( Map[Char, SortedSet[Int]]() ) { (m, i) => m += ( s(i) -> (m.getOrElse(s(i), SortedSet[Int]()) += i)) } } }
-
// the only difference comes to the operator import scala.collection.immutable.SortedMap import scala.collection.immutable.SortedSet object Ex2 extends App { def indexes(s: String) = { s.indices.foldLeft( SortedMap[Char, Set[Int]]() ) { (m, i) => m + ( s(i) -> (m.getOrElse(s(i), SortedSet[Int]()) + i)) } } }
-
def mkString[T](s: Seq[T], seq: String = ", "): String = s.map(_.toString) reduceLeft(_.toString + seq + _.toString)
Pattern matching is a powerful mechanism that has a number of applications: switch statements, type inquiry, and “destructuring” (getting at the parts of complex expressions). Case classes are optimized to work with pattern matching.
The equivalent of the C-style switch statement in Scala:
var sign = ...
val ch: Char = ...
ch match {
case '+' => sign = 1
case '-' => sign =-1
case _ => sign =0 // catch-all pattern
}
// can be written as
sign = ch match {
case '+' => 1
case '-' => -1
case _ => 0
}
// use | to separate multiple alternatives
prefix match {
case "0" | "0x" | "0X" =>...
...
}
// use match statement with any types
color match {
case Color.RED => ...
case Color.BLACK => ...
...
}
If no pattern matches, a MatchError is thrown.
Suppose we want to extend our example to match all digits. In a C-style switch statement, you would simply add multiple case labels, for example case '0': case '1': ... case '9':. (Except that, of course, you can’t use ... but must write out all ten cases explicitly.) In Scala, you add a guard clause
to a pattern:
ch match {
case _ if Character.isDigit(ch) => digit = Character.digit(ch, 10)
case '+' => sign = 1
case '-' => sign = -1
case _ => sign =0
}
The guard clause can be any Boolean condition.
If the case keyword is followed by a variable name, then the match expression is assigned to that variable.
str(i) match {
case '+' => sign = 1
case '-' => sign = -1
case ch => digit = Character.digit(ch, 10)
}
// use the variable name in a guard
str(i) match {
case ch if Character.isDigit(ch) => digit = Character.digit(ch, 10)
...
}
You can match on the type of an expression:
obj match {
case x: Int => x
case s: String => Integer.parseInt(s)
case _: BigInt => Int.MaxValue
case _ => 0
}
In Scala, this form is preferred to using the isInstanceOf
operator. Note the variable names in the patterns. In the first pattern, the match is bound to x as an Int, and in the second pattern, it is bound to s as a String. No asInstanceOf
casts are needed!
To match an array against its contents, use Array expressions in the patterns, like this:
arr match {
case Array(0) => "0"
case Array(x, y) => s"$x, $y"
case Array(0, _*) => "0 ..."
case _ => "something else"
}
The first pattern matches the array containing 0. The second pattern matches any array with two elements, and it binds the variables x and y to the elements. The third pattern matches any array starting with zero.
If you want to bind a variable argument match _* to a variable, use the @ notation like this:
case Array(x, rest @ _*) => rest.min
You can match lists in the same way, with List expressions. Alternatively, you can use the :: operator:
lst match {
case 0 :: Nil => "0"
case x :: y :: Nil => s"$x, $y"
case 0 :: tail => "0 ..."
case _ => "something else"
}
With tuples, use the tuple notation in the pattern:
pair match {
case (0, _) => "0 ..."
case (y, 0) => s"$y 0"
case _ => "neither is 0"
}
Again, note how the variables are bound to parts of the list or tuple. Since these bindings give you easy access to parts of a complex structure, this operation is called destructuring.
In the preceding section, you have seen how patterns can match arrays, lists, and tuples. These capabilities are provided by extractors—objects with an unapply
or unapplySeq
method that extract values from an object. The unapply method is provided to extract a fixed number of objects, while unapplySeq extracts a sequence whose length can vary. For example, consider the expression
arr match {
case Array(x, 0) => x
case Array(x, rest @ _*) => rest.min
...
}
The Array companion object is an extractor—it defines an unapplySeq method. That method is called with the expression that is being matched, not with what appear to be the parameters in the pattern. In the first case, the match succeeds if the array has length 2 and the second element is zero. In that case, the initial array element is assigned to x.
In the preceding sections, you have seen how patterns can contain variables. You can use these patterns inside variable declarations. For example,
val (x, y) = (1, 2) // simultaneously define x as 1 and y as 2
That is useful for functions that return a pair, for example:
val (q, r) = BigInt(10) /% 3 // The /% method returns a pair containing the quotient and the remainder, which are captured in the variables q and r
Traverse a map:
for ((k, v) <- System.getProperties())
println(s"$k -> $v)
In a for expression, match failures are silently ignored. For example, the following loop prints all keys with empty value, skipping over all others:
for ((k, "") <- System.getProperties())
println(k)
You can also use a guard. Note that the if
goes after the <-
symbol:
for ((k,v) <- System.getProperties() if v == "")
println(k)
Case classes are a special kind of classes that are optimized for use in pattern matching. In this example, we have two case classes that extend a regular (noncase) class:
abstract class Amount
case class Dollar(value: Double) extends Amount
case class Currency(value: Double, unit: String) extends Amount
You can also have case objects for singletons:
case object Nothing extends Amount
When we have an object of type Amount, we can use pattern matching to match the amount type and bind the property values to variables:
amt match {
case Dollar(v) => s"$$$v"
case Currency(_, u) => s"Oh noes, I got $u"
case Nothing => ""
}
The copy method of a case class makes a new object with the same values as an existing one. For example,
val amt = Currency(29.95, "EUR")
val price = amt.copy()
By itself, that isn’t very useful—after all, a Currency object is immutable, and one can just share the object reference. However, you can use named parameters to modify some of the properties:
val price = amt.copy(value = 19.95) // Currency(19.95, "EUR")
val price = amt.copy(unit = "CHF") // Currency(29.95, "EUR")