Learning Objectives

Provide more details of scala language

A Quick Guide of Scala

TL;DR: In this section, I will have a quick introduction of using Scala.

Basic Gramma

Start using Scala

After installed scala, you can type scala in command line and get result as follow:

$ scala
Welcome to Scala version 2.11.7
Type in expressions to have them evaluated.
Type :help for more information.

scala> println("Hello, World!")
Hello, World!

The synopsis of a varialbe is:

scala> val i:String = "abc"
i: String = abc

val means it it is immutable variable, you can use "var" to define a mutable variable
i is the name of this variable
String is the type of this string, it can be omitted here
"abc" is the value of this variable

Define a function:

scala> def foo(v0:Int, v1:Int):Int = {
     |     println(v0 max v1)
     |     v0 + v1
     | }
foo: (v0: Int, v1: Int)Int

scala> foo(1, 2)
2
res0: Int = 3

Define a class:

scala> class Foo(a:String, b:Int) {
     |     def length = a.length
     | }
defined class Foo

scala> val foo:Foo = new Foo("Hello, World!", 3)
foo: Foo = Foo@6438a396

scala> println(foo.length)
13

Define a case class:

scala> case class Foo(a:String, b:Int)
defined class Foo

scala> val foo:Foo = Foo(a = "Hello, World!", b = 3)
foo: Foo = Foo(Hello, World!,3)

scala> println(foo.a)
Hello, World!

Differences between case class and class

Define an Object

scala> object Foo {
     |     def greeting() {
     |         println("Greeting from Foo")
     |     }
     | }
defined object Foo

scala> Foo.greeting()
Greeting from Foo

Functions/variables in Object is similar to the static function and variable in Java.

What is ought to be highligted is the use of "apply". SomeObject.apply(v:Int) equals SomeObject(v:Int)

scala> :paste
// Entering paste mode (ctrl-D to finish)

case class Foo(a:String, b:Int)
object Foo {
    def apply(a:String): Foo =
        Foo(a, a.length)
}

// Exiting paste mode, now interpreting.

defined class Foo
defined object Foo

scala> val foo = Foo("Hello, World!")
foo: Foo = Foo(Hello, World!,13)

Finally, we should know the usage of code block.

We can create a code block anywhere, and the last line is the result of this block.

For example,

def foo(i:Int) = {
    println(s"value: $i")
    i * 2
}

val newList = List[Int](1, 2, 3).map(i => foo(i))

We can use the follow lines instead:

val newList = List[Int](1, 2, 3).map(i => {
    println(s"value: $i")
    i * 2
})

A better practice here is:

val newList = List[Int](1, 2, 3).map{i =>
    println(s"value: $i")
    i * 2
}

Case Study of some Common Types

Option, Some, None

We can use null in Scala as null pointer, but it is not recommended. We are supposed to use Option[SomeType] to indicate this variable is optional.

We can assueme every variable without Option are not null pointer if we are not calling java code. This help us reduce a lot of code.

If we wanna to get a variable with Option, here are two method

val oi = Option(1)
val i = oi match {
    case Some(ri) => ri
    case None => -1
}
println(i)

Besides, we can also use method "isDefined/isEmpty".

val oi = Option(1)
if(oi.isDefined) {
    println(s"oi: ${oi.get}")
} else {
    println("oi is empty")
}

What should be highlighted is Option(null) returns None, but Some(null) is Some(null) which is not equals None.

match is a useful reserved words, we can use it in various of situations

Firstly, we can use it as "switch" & "case" in some other programming languages.

true match {
    case true => println("true")
    case false => println("false")
}

Secondly, we can find it by the type of the data,

case class A(i:Int,j:Double)
case class B(a:A, k:Double)
val data = B(A(1,2.0),3.14)
data match {
    case B(A(_,v),_) =>
        println(s"required value: $v")
    case _ =>
        println("match failed")
}

Given a case class B, but we only wish to retrievee the value B.a.j, we can use "_" as placeholder.

Common methods in List, Array, Set, and so on

In scala, we always transfer the List( Array, Set, Map etc.) from one status to another status. the methods of

toList, toArray, toSet -- convert each other
par -- Parallelize List, Array and Map, the result of Seq[Int]().par is ParSeq[Int], you will able to process each element in parallel when you are using foreach, map etc., and unable to call "sort" before you are using "toList".
distinct -- Removes duplicate elements
foreach -- Process each element and return nothing

List[Int](1,2,3).foreach{ i =>
    println(i)
}

It wil print 1, 2, 3 in order

List[Int](1,2,3).par.foreach{ i =>
    println(i)
}

It will print 1, 2, 3, but the order is not guaranteed.

map -- Process each element and construct a List using return value

List[Int](1,2,3).map{ i => i + 1}

It will return List[Int](2,3,4)

The result of List[A]().map(some-oper-return-type-B) is List[B], while the result of Array[A]().map map is Array[B].

flatten -- The flatten method takes a list of lists and flattens it out to a single list:

scala> List[List[Int]](List(1,2),List(3,4)).flatten
res1: List[Int] = List(1, 2, 3, 4)

scala> List[Option[Integer]](Some(1),Some[Integer](null),Some(2),None,Some(3)).flatten
res2: List[Integer] = List(1, null, 2, 3)

flatMap -- The flatMap is similar to map, but it takes a function returning a list of elements as its right operand. It applies the function to each list element and returns the concatenation of all function results. The result equals to map + flatten
collect -- The iterator obtained from applying the partial function to every element in it for which it is defined and collecting the results.

scala> List(1,2,3.4,"str") collect {
     |   case i:Int => (i * 2).toString
     |   case f:Double => f.toString
     | }
res0: List[String] = List(2, 4, 3.4)

The function match elements in Int and Double, process them and return the value, but ignore string elements.

filter -- Filter this list

scala> List(1,2,3).filter(_ % 2 == 0)
res1: List[Int] = List(2)

filterNot -- Similar to filter

scala> List(1,2,3).filterNot(_ % 2 == 0)
res2: List[Int] = List(1, 3)

forall -- Return true if All elements are return true by the partial function. It will immediately return once one element returns false, and ignore the rest elements.

scala> List(2,1,0,-1).forall{ i =>
     |   val res = i > 0
     |   println(s"$i > 0? $res")
     |   res
     | }
2 > 0? true
1 > 0? true
0 > 0? false
res0: Boolean = false

exists -- Return true if there are at least One element returns true.

scala> List(2,1,0,-1).exists{ i =>
     |   val res = i <= 0
     |   println(s"$i <= 0? $res")
     |   res
     | }
2 <= 0? false
1 <= 0? false
0 <= 0? true
res2: Boolean = true

find -- Return the first element returns true by the partial function. Return None if no elemet found.

scala> List(2,1,0,-1).find{ i =>
     |   val res = i <= 0
     |   println(s"$i <= 0? $res")
     |   res
     | }
2 <= 0? false
1 <= 0? false
0 <= 0? true
res3: Option[Int] = Some(0)

sortWith -- sort the elements

scala> List(1,3,2).sortWith((leftOne,rightOne) => leftOne > rightOne)
res5: List[Int] = List(3, 2, 1)

zipWithIndex --

List("a","b").zipWithIndex.foreach{ kv:(String,Int) => println(s"k:${kv._1}, v:${kv._2}")}

It will rebuild a List with index

k:a, v:0
k:b, v:1

for - Scala's keyword for can be used in various of situations.

Basically,

for{
  i <- List(1,2,3)
} yield (i,i+1)

It equals:

List(1,2,3).map(i => (i, i+1))

Besides,

for{
  i <- List(1,2,3)
  j <- List(4,5,6)
} yield (i,j)

We will get the cartesian product of List(1,2,3) and List(4,5,6): List((1,4), (1,5), (1,6), (2,4), (2,5), (2,6), (3,4), (3,5), (3,6))

We can add a filter in condition:

for{
  i <- List(1,2,3)
  if i != 1
  j <- List(4,5,6)
  if i * j % 2 == 1
} yield (i,j)

the result is : List((3,5))

Another usage of for is as follow:

Let's define variables as follow:

val a = Some(1)
val b = Some(2)
val c = Some(3)

We can execute like this:

for {
    i <- a
    j <- b
    k <- c
    r <- {
        println(s"i: $i, j:$i, k:$k")
        Some(i * j * k)
    }
} yield r

The response is:

i: 1, j:1, k:3
res9: Option[Int] = Some(6)

Let's define b as None:

scala> val b:Option[Int] = None
b: Option[Int] = None

scala> for {
     |   i <- a
     |   j <- b
     |   k <- c
     |   r <- {
     |           println(s"i: $i, j:$i, k:$k")
     |           Some(i * j * k)
     |   }
     | } yield r
res14: Option[Int] = None

while - Similar to while in java

var i = 0
while ({
    i = i + 1
    i < 1000
}){
    // body of while
    println(s"i: $i")
}

to, until — (1 to 10) will generate a Seq, with the content of (1,2,3,4…10), (0 until 10) will generate a sequence from 0 to 9. With some test, (0 until 1000).map(xxx) appears to be slower than var i=0; while( i < 1000) { i += 1; sth. else}, but if the body of map is pretty heavy, this cost can be ignored.
headOption - Get the head of one list, return None if this list is empty
head - Get the head of one list, throw exception if this list is empty
take -- Get first at most N elements. (from left to right)

scala> List(1,2,3).take(2)
res0: List[Int] = List(1, 2)

scala> List(1,2).take(3)
res1: List[Int] = List(1, 2)

drop -- Drop first at most N elements.

scala> List(1,2,3).drop(2)
res2: List[Int] = List(3)

scala> List(1,2).drop(3)
res3: List[Int] = List()

dropRight will drop elements from right to left.

slice -- Return list in [start-offset, end-offset)

scala> List(1,2,3).slice(1,2)
res7: List[Int] = List(2)

scala> List(1,2,3).slice(2,2)
res8: List[Int] = List()

val offset = 1
val size = 3
List(1,2,3,4,5).slice(offset, size + offset)

If the end-offset is greater than the length of this list, it will not throw exception.

splitAt -- Split this list into two from offset i

scala> List(1,2,3).splitAt(1)
res10: (List[Int], List[Int]) = (List(1),List(2, 3))

groupBy -- Partitions a list into a map of collections according to a discriminator function

scala> List(1,2,3).groupBy(i => if(i % 2 == 0) "even" else "odd" )
res11: scala.collection.immutable.Map[String,List[Int]] = Map(odd -> List(1, 3), even -> List(2))

partition -- Splits a list into a pair of collections; one with elements that satisfy the predicate, the other with elements that do not, giving the pair of collections (xs filter p, xs.filterNot p).

scala> List(1,2,3).partition(_ % 2 == 0)
res12: (List[Int], List[Int]) = (List(2),List(1, 3))

grouped -- The grouped method chunks its elements into increments.

scala> List(1,2,3,4,5).grouped(2)
res13: Iterator[List[Int]] = Iterator(List(1, 2), List(3, 4), List(5))

Credit to Yu Jing PDF(with copyright issue): https://doc.argcv.com/scala/Programming.in.Scala.2ed.pdf