// Scala Lecture 4
//=================
// Polymorphic Types
//===================
// You do not want to write functions like contains, first,
// length and so on for every type of lists.
def length_string_list(lst: List[String]): Int = lst match {
case Nil => 0
case x::xs => 1 + length_string_list(xs)
}
def length_int_list(lst: List[Int]): Int = lst match {
case Nil => 0
case x::xs => 1 + length_int_list(xs)
}
length_string_list(List("1", "2", "3", "4"))
length_int_list(List(1, 2, 3, 4))
//-----
def length[A](lst: List[A]): Int = lst match {
case Nil => 0
case x::xs => 1 + length(xs)
}
length(List("1", "2", "3", "4"))
length(List(1, 2, 3, 4))
def map[A, B](lst: List[A], f: A => B): List[B] = lst match {
case Nil => Nil
case x::xs => f(x)::map(xs, f)
}
map(List(1, 2, 3, 4), (x: Int) => x * x)
// Remember?
def first[A, B](xs: List[A], f: A => Option[B]) : Option[B] = ...
// distinct / distinctBy
val ls = List(1,2,3,3,2,4,3,2,1)
ls.distinct
def distinctBy[B, C](xs: List[B],
f: B => C,
acc: List[C] = Nil): List[B] = xs match {
case Nil => Nil
case x::xs => {
val res = f(x)
if (acc.contains(res)) distinctBy(xs, f, acc)
else x::distinctBy(xs, f, res::acc)
}
}
// distinctBy with the identity function is
// just distinct
distinctBy(ls, (x: Int) => x)
val cs = List('A', 'b', 'a', 'c', 'B', 'D', 'd')
distinctBy(cs, (c:Char) => c.toUpper)
// Type inference is local in Scala
def id[T](x: T) : T = x
val x = id(322) // Int
val y = id("hey") // String
val z = id(Set(1,2,3,4)) // Set[Int]
// The type variable concept in Scala can get really complicated.
//
// - variance (OO)
// - bounds (subtyping)
// - quantification
// Java has issues with this too: Java allows
// to write the following incorrect code, and
// only recovers by raising an exception
// at runtime.
// Object[] arr = new Integer[10];
// arr[0] = "Hello World";
// Scala gives you a compile-time error
var arr = Array[Int]()
arr(0) = "Hello World"
//
// Object Oriented Programming in Scala
//
// =====================================
abstract class Animal
case class Bird(name: String) extends Animal
case class Mammal(name: String) extends Animal
case class Reptile(name: String) extends Animal
println(Bird("Sparrow"))
println(Bird("Sparrow").toString)
// you can override methods
case class Bird(name: String) extends Animal {
override def toString = name
}
// There is a very convenient short-hand notation
// for constructors
class Fraction(x: Int, y: Int) {
def numer = x
def denom = y
}
case class Fraction(numer: Int, denom: Int)
val half = Fraction(1, 2)
half.denom
// In mandelbrot.scala I used complex (imaginary) numbers
// and implemented the usual arithmetic operations for complex
// numbers.
case class Complex(re: Double, im: Double) {
// represents the complex number re + im * i
def +(that: Complex) = Complex(this.re + that.re, this.im + that.im)
def -(that: Complex) = Complex(this.re - that.re, this.im - that.im)
def *(that: Complex) = Complex(this.re * that.re - this.im * that.im,
this.re * that.im + that.re * this.im)
def *(that: Double) = Complex(this.re * that, this.im * that)
def abs = Math.sqrt(this.re * this.re + this.im * this.im)
}
val test = Complex(1, 2) + Complex (3, 4)
// this could have equally been written as
val test = Complex(1, 2).+(Complex (3, 4))
// this applies to all methods, but requires
import scala.language.postfixOps
List(5, 2, 3, 4).sorted
List(5, 2, 3, 4) sorted
// ...to allow the notation n + m * i
import scala.language.implicitConversions
object i extends Complex(0, 1)
implicit def double2complex(re: Double) = Complex(re, 0)
val inum1 = -2.0 + -1.5 * i
val inum2 = 1.0 + 1.5 * i
// All is public by default....so no public is needed.
// You can have the usual restrictions about private
// values and methods, if you are MUTABLE !!!
case class BankAccount(init: Int) {
private var balance = init
def deposit(amount: Int): Unit = {
if (amount > 0) balance = balance + amount
}
def withdraw(amount: Int): Int =
if (0 < amount && amount <= balance) {
balance = balance - amount
balance
} else throw new Error("insufficient funds")
}
// BUT since we are completely IMMUTABLE, this is
// virtually of not concern to us.
// DFAs in Scala
import scala.util.Try
// A is the state type
// C is the input (usually characters)
case class DFA[A, C](start: A, // starting state
delta: (A, C) => A, // transition function
fins: A => Boolean) { // final states (Set)
def deltas(q: A, s: List[C]) : A = s match {
case Nil => q
case c::cs => deltas(delta(q, c), cs)
}
def accepts(s: List[C]) : Boolean =
Try(fins(deltas(start, s))) getOrElse false
}
// the example shown in the handout
abstract class State
case object Q0 extends State
case object Q1 extends State
case object Q2 extends State
case object Q3 extends State
case object Q4 extends State
val delta : (State, Char) => State =
{ case (Q0, 'a') => Q1
case (Q0, 'b') => Q2
case (Q1, 'a') => Q4
case (Q1, 'b') => Q2
case (Q2, 'a') => Q3
case (Q2, 'b') => Q2
case (Q3, 'a') => Q4
case (Q3, 'b') => Q0
case (Q4, 'a') => Q4
case (Q4, 'b') => Q4
case _ => throw new Exception("Undefined") }
val dfa = DFA(Q0, delta, Set[State](Q4))
dfa.accepts("abaaa".toList) // true
dfa.accepts("bbabaab".toList) // true
dfa.accepts("baba".toList) // false
dfa.accepts("abc".toList) // false
// another DFA with a Sink state
abstract class S
case object S0 extends S
case object S1 extends S
case object S2 extends S
case object Sink extends S
// transition function with a sink state
val sigma : (S, Char) => S =
{ case (S0, 'a') => S1
case (S1, 'a') => S2
case _ => Sink
}
val dfa2 = DFA(S0, sigma, Set[S](S2))
dfa2.accepts("aa".toList) // true
dfa2.accepts("".toList) // false
dfa2.accepts("ab".toList) // false
// we could also have a dfa for numbers
val sigmai : (S, Int) => S =
{ case (S0, 1) => S1
case (S1, 1) => S2
case _ => Sink
}
val dfa3 = DFA(S0, sigmai, Set[S](S2))
dfa3.accepts(List(1, 1)) // true
dfa3.accepts(Nil) // false
dfa3.accepts(List(1, 2)) // false
// NFAs (Nondeterministic Finite Automata)
case class NFA[A, C](starts: Set[A], // starting states
delta: (A, C) => Set[A], // transition function
fins: A => Boolean) { // final states
// given a state and a character, what is the set of
// next states? if there is none => empty set
def next(q: A, c: C) : Set[A] =
Try(delta(q, c)) getOrElse Set[A]()
// depth-first version of accepts
def search(q: A, s: List[C]) : Boolean = s match {
case Nil => fins(q)
case c::cs => next(q, c).exists(search(_, cs))
}
def accepts(s: List[C]) : Boolean =
starts.exists(search(_, s))
}
// NFA examples
val nfa_trans1 : (State, Char) => Set[State] =
{ case (Q0, 'a') => Set(Q0, Q1)
case (Q0, 'b') => Set(Q2)
case (Q1, 'a') => Set(Q1)
case (Q2, 'b') => Set(Q2) }
val nfa = NFA(Set[State](Q0), nfa_trans1, Set[State](Q2))
nfa.accepts("aa".toList) // false
nfa.accepts("aaaaa".toList) // false
nfa.accepts("aaaaab".toList) // true
nfa.accepts("aaaaabbb".toList) // true
nfa.accepts("aaaaabbbaaa".toList) // false
nfa.accepts("ac".toList) // false
// Q: Why the kerfuffle about the polymorphic types in DFAs/NFAs?
// A: Subset construction
def subset[A, C](nfa: NFA[A, C]) : DFA[Set[A], C] = {
DFA(nfa.starts,
{ case (qs, c) => nfa.nexts(qs, c) },
_.exists(nfa.fins))
}
subset(nfa1).accepts("aa".toList) // false
subset(nfa1).accepts("aaaaa".toList) // false
subset(nfa1).accepts("aaaaab".toList) // true
subset(nfa1).accepts("aaaaabbb".toList) // true
subset(nfa1).accepts("aaaaabbbaaa".toList) // false
subset(nfa1).accepts("ac".toList) // false
// Cool Stuff in Scala
//=====================
// Implicits or How to Pimp my Library
//=====================================
//
// For example adding your own methods to Strings:
// Imagine you want to increment strings, like
//
// "HAL".increment
//
// you can avoid ugly fudges, like a MyString, by
// using implicit conversions.
implicit class MyString(s: String) {
def increment = for (c <- s) yield (c + 1).toChar
}
"HAL".increment
// Regular expressions - the power of DSLs in Scala
//==================================================
abstract class Rexp
case object ZERO extends Rexp // nothing
case object ONE extends Rexp // the empty string
case class CHAR(c: Char) extends Rexp // a character c
case class ALT(r1: Rexp, r2: Rexp) extends Rexp // alternative r1 + r2
case class SEQ(r1: Rexp, r2: Rexp) extends Rexp // sequence r1 . r2
case class STAR(r: Rexp) extends Rexp // star r*
// (ab)*
val r0 = STAR(SEQ(CHAR('a'), CHAR('b')))
// some convenience for typing in regular expressions
import scala.language.implicitConversions
import scala.language.reflectiveCalls
def charlist2rexp(s: List[Char]): Rexp = s match {
case Nil => ONE
case c::Nil => CHAR(c)
case c::s => SEQ(CHAR(c), charlist2rexp(s))
}
implicit def string2rexp(s: String): Rexp = charlist2rexp(s.toList)
val r1 = STAR("ab")
val r2 = STAR(ALT("ab", "baa baa black sheep"))
val r3 = STAR(SEQ("ab", ALT("a", "b")))
implicit def RexpOps (r: Rexp) = new {
def | (s: Rexp) = ALT(r, s)
def % = STAR(r)
def ~ (s: Rexp) = SEQ(r, s)
}
implicit def stringOps (s: String) = new {
def | (r: Rexp) = ALT(s, r)
def | (r: String) = ALT(s, r)
def % = STAR(s)
def ~ (r: Rexp) = SEQ(s, r)
def ~ (r: String) = SEQ(s, r)
}
//example regular expressions
val digit = "0" | "1" | "2" | "3" | "4" | "5" | "6" | "7" | "8" | "9"
val sign = "+" | "-" | ""
val number = sign ~ digit ~ digit.%
// Lazy Evaluation
//=================
//
// do not evaluate arguments just yet
def time_needed[T](i: Int, code: => T) = {
val start = System.nanoTime()
for (j <- 1 to i) code
val end = System.nanoTime()
(end - start)/(i * 1.0e9)
}
// same examples using the internal regexes
val evil = "(a*)*b"
("a" * 10 ++ "b").matches(evil)
("a" * 10).matches(evil)
("a" * 10000).matches(evil)
("a" * 20000).matches(evil)
time_needed(2, ("a" * 10000).matches(evil))