An example of functional programming in scala - scala

I'm studying scala. It's very promising, thanks to Odersky and all the other authors for their great work.
I took a euler problem (http://projecteuler.net/) to have a more-then-minimal example. And I'm trying to go the functional way. So this is not a "please answer me immediatly or my boss will kill me" but a "please if you've got time, can you help a imperative language programmer to take a journey in the functional world?"
Problem: I want a class for poker hands. A poker Hand is composed by a number of Card, from 0 to 5. I'd like to build the list of Cards one and for all, that is: my Hand class will be immutable, if I want to add a card, then I create a new Hand object.
So I need a collection of Card that can be created as "val", not as var.
First step: constructors, one for each number of cards. But Card's collection is handled in each constructor, so I must have it as var!
Here's the code, Card class is simply a Suit and a Value, passed to constructor as a string ("5S" is the 5 of spades):
class Hand(mycards : List[Card]) {
// this should be val, I guess
private var cards : List[Card] = {
if (mycards.length>5)
throw new IllegalArgumentException(
"Illegal number of cards: " + mycards.length);
sortCards(mycards)
}
// full hand constructor
def this(a : String, b : String, c : String, d : String, e : String) = {
this(Nil)
// assign cards
val cardBuffer = new ListBuffer[Card]()
if ( a!=null ) cardBuffer += new Card(a)
if ( b!=null ) cardBuffer += new Card(b)
if ( c!=null ) cardBuffer += new Card(c)
if ( d!=null ) cardBuffer += new Card(d)
if ( e!=null ) cardBuffer += new Card(e)
cards = sortCards(cardBuffer.toList)
}
// hand with less then 5 cards
def this(a : String, b : String, c : String, d : String) = this(a,b,c,d,null)
def this(a : String, b : String, c : String) = this(a, b, c, null)
def this(a : String, b : String) = this(a, b, null)
def this(a : String) = this(a, null)
def this() = this(Nil)
/* removed */
}
Do you know how to make it the true functional way?
Thanks.
PS: if you really want to know, it's problem 54.

My answer is not about functional aspect of scala, but your code is possible to write shortly using scala sugar:
class Hand(val mycards: List[Card]) {
require (mycards.size <= 5,"can't be more than five cards")
def this(input: String*) = {
this(input.map(c => new Card(c)).toList)
}
}
input: String* in auxiliary constructor says that you can have variable number of arguments (even thousand of strings).
I'm getting input and invoke creation for each new Card with map function, and then pass result to parent constructor which has it's own requirement.
(BTW, mapping from string to Card can be done anonymously, in that manner: this(input.map(new Card(_)).toList))
class Hand(val mycards: List[Card]) {...
Is equable to
class Hand(cards: List[Card]) {
val mycards = cards
...
From now on, if you will try to create more than five cards in hand you'll get java.lang.IllegalArgumentException:
scala> class Card(s: String) {println("Im a :"+s)}
defined class Card
scala> new Hand("one","two","three","four","five","six")
Im a :one
Im a :two
Im a :three
Im a :four
Im a :five
Im a :six
java.lang.IllegalArgumentException: requirement failed: can't be more than five card
at scala.Predef$.require(Predef.scala:157)
at Hand.<init>(<console>:9)

Well, the the var in the code below comes from you not initializing cards from the main constructor:
// this should be val, I guess
private var cards : List[Card] = {
if (mycards.length>5)
throw new IllegalArgumentException(
"Illegal number of cards: " + mycards.length);
sortCards(mycards)
}
So what you need to do is fix the secondary constructor:
// full hand constructor
def this(a : String, b : String, c : String, d : String, e : String) = {
this(Nil)
// assign cards
val cardBuffer = new ListBuffer[Card]()
if ( a!=null ) cardBuffer += new Card(a)
if ( b!=null ) cardBuffer += new Card(b)
if ( c!=null ) cardBuffer += new Card(c)
if ( d!=null ) cardBuffer += new Card(d)
if ( e!=null ) cardBuffer += new Card(e)
cards = sortCards(cardBuffer.toList)
}
THe problemn is simple: you want a list of cards formed by non-null Strings. If I were you, I'd just avoid passing nulls, but... Anyway, the best way to handle that is to convert this into options. The conversion is simple: Option(a) will return Some(a) is a is not null, and None if it is. If you compose a list of that, you can then flatten it to remove the None and convert Some(a) back into a. In other words:
def this(a : String, b : String, c : String, d : String, e : String) =
this(List(a, b, c, d, e).map(Option(_)).flatten.map(Card(_)))

Because in this example you are only allowed to use five cards I would check this at compile time with the use of a Tuple5:
type HandType = (ACard, ACard, ACard, ACard, ACard)
case class Hand(h: HandType)
abstract class ACard {
def exists: Boolean
}
case class Card(value: Int, color: Color) extends ACard {
def exists = true
}
case object NoCard extends ACard {
def exists = false
}
abstract class Color(val c: Int)
case object H extends Color(1)
case object C extends Color(2)
case object S extends Color(3)
case object D extends Color(4)
case object NoColor extends Color(0)
implicit def tuple2Card(t: (Int, Color)) = Card(t._1, t._2)
val h1 = Hand((Card(4, H), Card(6, S), Card(2, S), Card(8, D), NoCard))
val h2 = Hand((4 -> H, 6 -> S, 2 -> S, 8 -> D, NoCard))
println(h1)
println(h2)
h1.h.productIterator foreach { c => println(c.asInstanceOf[ACard].exists) }
Of course in another example when there can be an unspecific number of elements you need to check them at runtime. productIterator only returns a Iterator[Any] but when you use your cards directly by the field-identifiers (_1 .. _5) you will get an ACard.

Firstly, null is evil, use Option instead. Secondly, Scala supports default parameters. So instead of creating all the constructors, you might just wanna use one of them like this:
def this(a: String = null, ..., e: String = null) = ...
or with Option, which is safer.
def this(a: Option[String] = None, ..., e: Option[String] = None) = {
this(Nil)
val cardBuffer = new ListBuffer[Card]()
a foreach { cardBuffer += new Card(_) }
b foreach { cardBuffer += new Card(_) }
c foreach { cardBuffer += new Card(_) }
d foreach { cardBuffer += new Card(_) }
e foreach { cardBuffer += new Card(_) }
cards = sortCards(cardBuffer.toList)
}
So the cards are only added to the buffer if they "exist".

First, we need to fix a compile error in your cards field definition.
Note that in Scala you usually don't have to declare fields. Main constructor parameters already are fields! So, this can be written simpler:
class Hand(cards : List[Card]) {
if (cards.length>5)
throw new IllegalArgumentException(
"Illegal number of cards: " + mycards.length);
Now we have mutability problem. If you want to program in functional style, everything should be immutable, so the "full hand constructor" is not functional at all: it has 6 side-effecting operations, last of which does not compile.
In functional setting, an object can't be modified after its constructor has terminated, so all the code after this(Nil) is useless. You already said that cards is Nil, what else do you want?! So, all the computations have to happen before the main constructor call. We'd like to remove this(Nil) from the top and add this(sortCards(cardBuffer.toList)) to the bottom. Unfortunately, Scala does not allow that. Fortunately, it allows more options to achieve the same than java: first, you can use a nested block like this:
this({
val cardBuffer = ... /* terrible imperativeness */
sortCards(cardBuffer.toList)
})
second, you can use apply method instead of a constructor:
object Hand {
def apply(a : String, b : String, c : String, d : String, e : String) = {
val cardBuffer = ... /* terrible imperativeness */
new Hand(sortCards(cardBuffer.toList))
}
}
Now, let's start getting rid of imperative ListBuffer. First improvement would be to use var of type List[Card]. Making mutability more local will help to remove it later:
// assign cards
var cards = Nil
if ( e!=null ) cards = new Card(e) :: cards
if ( d!=null ) cards = new Card(d) :: cards
if ( c!=null ) cards = new Card(c) :: cards
if ( b!=null ) cards = new Card(b) :: cards
if ( a!=null ) cards = new Card(a) :: cards
sortCards(cards)
Okay, now we can see what exactly we are mutating and can easily remove that mutability:
val fromE = if ( e!=null ) new Card(e) :: Nil else Nil
val fromD = if ( d!=null ) new Card(d) :: fromE else fromE
val fromC = if ( c!=null ) new Card(c) :: fromD else fromD
val fromB = if ( b!=null ) new Card(b) :: fromC else fromC
val fromA = if ( a!=null ) new Card(a) :: fromB else fromB
sortCards(fromA)
Now we have a fair amount of code duplication. Let's remove that in a brute-force way (find a long duplicating piece of code and extract function)!
def prependCard(x : String, cards : List[Card]) =
if ( x!=null ) new Card(x) :: cards else cards
val cards = prependCard(a, prependCard(b,
prependCard(c, prependCard(d,
prependCard(e, Nil)
))
))
sortCards(cards)
Next, very important, transformation would be to replace nullable references with the values of Option type, or remove the empty card concept altogether.
Update:
As requested, I am adding an example of usage of the apply method. Notice that it is declared in object Hand, not class Hand, so it doesn't need an instance of the class (it's similar to static method in java). We just apply the object to parameters: val hand = Hand("5S", "5S", "5S", "5S", "5S").

Attempt using varargs, overloaded + operator, repeated addition in constructor, and Set to eliminate duplicate cards.
package poker
class Hand(private val cards:Set[Card] = Set.empty[Card]) {
def + (card:Card) = {
val hand = new Hand(cards + card)
require(hand.length > length, "Card %s duplicated".format(card))
require(hand.length <= Hand.maxLength, "Hand length > %d".format(Hand.maxLength))
hand
}
def length = cards.size
override def toString = cards.mkString("(", ",", ")")
}
object Hand {
val maxLength = 5
def apply(cards:Card*):Hand = cards.foldLeft(Hand())(_ + _)
private def apply() = new Hand()
}
//-----------------------------------------------------------------------------------------------//
class Card private (override val toString:String)
object Card {
def apply(card:String) = {
require(cardMap.contains(card), "Card %s does not exist".format(card))
cardMap(card)
}
def cards = cardMap.values.toList
private val cardMap = {
val ranks = Range(2,9).inclusive.map { _.toString } ++ List("T", "J", "Q", "K", "A")
val suits = List("c","d","h","s")
(for(r <- ranks; s <- suits) yield (r + s -> new Card(r + s))).toMap
}
}
//-----------------------------------------------------------------------------------------------//
object Test extends App {
Array("1f", "Ac").foreach { s =>
try {
printf("Created card %s successfully\n",Card(s))
} catch {
case e:Exception => printf("Input string %s - %s \n", s, e.getMessage)
}
}
println
for(i <- 0 to 6) {
val cards = Card.cards.slice(0, i)
makeHand(cards)
}
println
val cards1 = List("Ac","Ad","Ac").map { Card(_) }
makeHand(cards1)
println
val hand1 = Hand(List("Ac","Ad").map { Card(_) }:_* )
val card = Card("Ah")
val hand2 = hand1 + card
printf("%s + %s = %s\n", hand1, card, hand2)
def makeHand(cards:List[Card]) =
try {
val hand = Hand(cards: _*)
printf("Created hand %s successfully\n",hand)
} catch {
case e:Exception => printf("Input %s - %s \n", cards, e.getMessage)
}
}

Related

Modifying generic maps in Scala

I'm new to the Scala landscape after spending the last 10 years in Java and the last ~year in Groovy. Hi Scala!
For the life of me I can't seem to get the following code snippet to compile, and its just complicated enough to the point where the Google Gods aren't helping me.
I have a map that will contain Strings for keys and Lists of Tuples for values. The tuples will be a String-Long pair. In Groovy this would look like:
Map<String,List<Tuple2<String,Long>>> data = [:]
I need to be able to add and modify keys and values for this map. Specifically, I need to:
Add to the List of Tuples for existing keys
If a key doesn't exist, instantiate a new List of Tuples, and then add the key and list as a map entry
In Groovy this would look like:
Map<String,List<String,Long>> data = [:]
def addData(String key, String message) {
Long currTime = System.currentTimestampInMillis()
Tuple2<String,Long> tuple = new Tuple2<String,Long>(message, tuple)
if(data.contains(key)) {
data.key << tuple
} else {
data[key] = new List<Tuple2<String,Long>>()
data.key << tuple
}
}
I'm trying to do this in Scala, albeit unsuccessfully.
My best attempt thus far:
object MapUtils {
// var data : Map[String,ListBuffer[(String,Long)]] = Map()
val data = collection.mutable.Map[String, ListBuffer[(String, Long)]]()
def addData(key : String, message : String) : Unit = {
val newTuple = (message, System.currentTimeMillis())
val optionalOldValue = data.get(key)
optionalOldValue match {
case Some(olderBufferList) => olderBufferList += newTuple
case None => data
.put(key, ListBuffer[(String, Long)](newTuple))
}
}
}
Complains with this compiler error on the case Some(olderBufferList) => olderBufferList += newTuple line:
value += is not a member of Any
Any ideas what I can do to get this compiling & working?
You are missing an import for ListBuffer. The following code works perfectly fine in 2.9.1 (tested on TryScala), 2.11.7 (tested on IDEOne) and 2.11.8. Note the only addition is the first line adding the import:
import collection.mutable.ListBuffer
object MapUtils {
// var data : Map[String,ListBuffer[(String,Long)]] = Map()
val data = collection.mutable.Map[String, ListBuffer[(String, Long)]]()
def addData(key : String, message : String) : Unit = {
val newTuple = (message, System.currentTimeMillis())
val optionalOldValue = data.get(key)
optionalOldValue match {
case Some(olderBufferList) => olderBufferList += newTuple
case None => data
.put(key, ListBuffer[(String, Long)](newTuple))
}
}
}
MapUtils.addData("123", "message 1")
MapUtils.addData("456", "message 2")
MapUtils.data
//=> Map(456 -> ListBuffer((message 2,1472925061065)), 123 -> ListBuffer((message 1,1472925060926)))
The short version for your needs will be:
val map = mutable.Map[String, ListBuffer[(String, Long)]]()
map.put(key, map.getOrElse(key, ListBuffer[(String, Long)]()) += ((message, System.currentTimeMillis())))
You have some syntax issues with your code, If I'll try to change addData it would look like this:
def addData(key : String, message : String) : Unit = {
val newTuple = (message, System.currentTimeMillis())
val optionalOldValue = map.get(key)
optionalOldValue match {
case Some(olderBufferList) => olderBufferList += newTuple
case None => map.put(key, ListBuffer[(String, Long)](newTuple))
}
}

How to aggregateByKey with custom class for frequency distribution?

I am trying to create a frequency distribution.
My data is in the following pattern (ColumnIndex, (Value, countOfValue)) of type (Int, (Any, Long)). For instance, (1, (A, 10)) means for column index 1, there are 10 A's.
My goal is to get the top 100 values for all my index's or Keys.
Right away I can make it less compute intensive for my workload by doing an initial filter:
val freqNumDist = numRDD.filter(x => x._2._2 > 1)
Now I found an interesting example of a class, here which seems to fit my use case:
class TopNList (val maxSize:Int) extends Serializable {
val topNCountsForColumnArray = new mutable.ArrayBuffer[(Any, Long)]
var lowestColumnCountIndex:Int = -1
var lowestValue = Long.MaxValue
def add(newValue:Any, newCount:Long): Unit = {
if (topNCountsForColumnArray.length < maxSize -1) {
topNCountsForColumnArray += ((newValue, newCount))
} else if (topNCountsForColumnArray.length == maxSize) {
updateLowestValue
} else {
if (newCount > lowestValue) {
topNCountsForColumnArray.insert(lowestColumnCountIndex, (newValue, newCount))
updateLowestValue
}
}
}
def updateLowestValue: Unit = {
var index = 0
topNCountsForColumnArray.foreach{ r =>
if (r._2 < lowestValue) {
lowestValue = r._2
lowestColumnCountIndex = index
}
index+=1
}
}
}
So Now What I was thinking was putting together an aggregateByKey to use this class in order to get my top 100 values! The problem is that I am unsure of how to use this class in aggregateByKey in order to accomplish this goal.
val initFreq:TopNList = new TopNList(100)
def freqSeq(u: (TopNList), v:(Double, Long)) = (
u.add(v._1, v._2)
)
def freqComb(u1: TopNList, u2: TopNList) = (
u2.topNCountsForColumnArray.foreach(r => u1.add(r._1, r._2))
)
val freqNumDist = numRDD.filter(x => x._2._2 > 1).aggregateByKey(initFreq)(freqSeq, freqComb)
The obvious problem is that nothing is returned by the functions I am using. So I am wondering how to modify this class or do I need to think about this in a whole new light and just cherry pick some of the functions out of this class and add them to the functions I am using for the aggregateByKey?
I'm either thinking about classes wrong or the entire aggregateByKey or both!
Your projections implementations (freqSeq, freqComb) return Unit while you expect them to return TopNList
If intentially keep the style of your solution, the relevant impl should be
def freqSeq(u: TopNList, v:(Any, Long)) : TopNList = {
u.add(v._1, v._2) // operation gives void result (Unit)
u // this one of TopNList type
}
def freqComb(u1: TopNList, u2: TopNList) : TopNList = {
u2.topNCountsForColumnArray.foreach (r => u1.add (r._1, r._2) )
u1
}
Just take a look on aggregateByKey signature of PairRDDFunctions, what does it expect for
def aggregateByKey[U](zeroValue : U)(seqOp : scala.Function2[U, V, U], combOp : scala.Function2[U, U, U])(implicit evidence$3 : scala.reflect.ClassTag[U]) : org.apache.spark.rdd.RDD[scala.Tuple2[K, U]] = { /* compiled code */ }

How to add 'Array[Ordered[Any]]' as a method parameter

Below is an implementation of Selection sort written in Scala.
The line ss.sort(arr) causes this error :
type mismatch; found : Array[String] required: Array[Ordered[Any]]
Since the type Ordered is inherited by StringOps should this type not be inferred ?
How can I add the array of Strings to sort() method ?
Here is the complete code :
object SelectionSortTest {
def main(args: Array[String]){
val arr = Array("Hello","World")
val ss = new SelectionSort()
ss.sort(arr)
}
}
class SelectionSort {
def sort(a : Array[Ordered[Any]]) = {
var N = a.length
for (i <- 0 until N) {
var min = i
for(j <- i + 1 until N){
if( less(a(j) , a(min))){
min = j
}
exchange(a , i , min)
}
}
}
def less(v : Ordered[Any] , w : Ordered[Any]) = {
v.compareTo(w) < 0
}
def exchange(a : Array[Ordered[Any]] , i : Integer , j : Integer) = {
var swap : Ordered[Any] = a(i)
a(i) = a(j)
a(j) = swap
}
}
Array is invariant. You cannot use an Array[A] as an Array[B] even if A is subtype of B. See here why: Why are Arrays invariant, but Lists covariant?
Neither is Ordered, so your implementation of less will not work either.
You should make your implementation generic the following way:
object SelectionSortTest {
def main(args: Array[String]){
val arr = Array("Hello","World")
val ss = new SelectionSort()
ss.sort(arr)
}
}
class SelectionSort {
def sort[T <% Ordered[T]](a : Array[T]) = {
var N = a.length
for (i <- 0 until N) {
var min = i
for(j <- i + 1 until N){
if(a(j) < a(min)){ // call less directly on Ordered[T]
min = j
}
exchange(a , i , min)
}
}
}
def exchange[T](a : Array[T] , i : Integer , j : Integer) = {
var swap = a(i)
a(i) = a(j)
a(j) = swap
}
}
The somewhat bizarre statement T <% Ordered[T] means "any type T that can be implicitly converted to Ordered[T]". This ensures that you can still use the less-than operator.
See this for details:
What are Scala context and view bounds?
The answer by #gzm0 (with some very nice links) suggests Ordered. I'm going to complement with an answer covering Ordering, which provides equivalent functionality without imposing on your classes as much.
Let's adjust the sort method to accept an array of type 'T' for which an Ordering implicit instance is defined.
def sort[T : Ordering](a: Array[T]) = {
val ord = implicitly[Ordering[T]]
import ord._ // now comparison operations such as '<' are available for 'T'
// ...
if (a(j) < a(min))
// ...
}
The [T : Ordering] and implicitly[Ordering[T]] combo is equivalent to an implicit parameter of type Ordering[T]:
def sort[T](a: Array[T])(implicit ord: Ordering[T]) = {
import ord._
// ...
}
Why is this useful?
Imagine you are provided with a case class Account(balance: Int) by some third party. You can now add an Ordering for it like so:
// somewhere in scope
implicit val accountOrdering = new Ordering[Account] {
def compare(x: Account, y: Account) = x.balance - y.balance
}
// or, more simply
implicit val accountOrdering: Ordering[Account] = Ordering by (_.balance)
As long as that instance is in scope, you should be able to use sort(accounts).
If you want to use some different ordering, you can also provide it explicitly, like so: sort(accounts)(otherOrdering).
Note that this isn't very different from providing an implicit conversion to Ordering (at least not within the context of this question).
Even though, when coding Scala, I'm used to prefer functional programming style (via combinators or recursion) over imperative style (via variables and iterations), THIS TIME, for this specific problem, old school imperative nested loops result in simpler and performant code.
I don't think falling back to imperative style is a mistake for certain classes of problems, such as sorting algorithms which usually transform the input buffer (more like a procedure) rather than resulting to a new sorted collection.
Here it is my solution:
package bitspoke.algo
import scala.math.Ordered
import scala.collection.mutable.Buffer
abstract class Sorter[T <% Ordered[T]] {
// algorithm provided by subclasses
def sort(buffer : Buffer[T]) : Unit
// check if the buffer is sorted
def sorted(buffer : Buffer[T]) = buffer.isEmpty || buffer.view.zip(buffer.tail).forall { t => t._2 > t._1 }
// swap elements in buffer
def swap(buffer : Buffer[T], i:Int, j:Int) {
val temp = buffer(i)
buffer(i) = buffer(j)
buffer(j) = temp
}
}
class SelectionSorter[T <% Ordered[T]] extends Sorter[T] {
def sort(buffer : Buffer[T]) : Unit = {
for (i <- 0 until buffer.length) {
var min = i
for (j <- i until buffer.length) {
if (buffer(j) < buffer(min))
min = j
}
swap(buffer, i, min)
}
}
}
As you can see, to achieve parametric polymorphism, rather than using java.lang.Comparable, I preferred scala.math.Ordered and Scala View Bounds rather than Upper Bounds. That's certainly works thanks to Scala Implicit Conversions of primitive types to Rich Wrappers.
You can write a client program as follows:
import bitspoke.algo._
import scala.collection.mutable._
val sorter = new SelectionSorter[Int]
val buffer = ArrayBuffer(3, 0, 4, 2, 1)
sorter.sort(buffer)
assert(sorter.sorted(buffer))

Scala - how to print case classes like (pretty printed) tree

I'm making a parser with Scala Combinators. It is awesome. What I end up with is a long list of entagled case classes, like: ClassDecl(Complex,List(VarDecl(Real,float), VarDecl(Imag,float))), just 100x longer. I was wondering if there is a good way to print case classes like these in a tree-like fashion so that it's easier to read..? (or some other form of Pretty Print)
ClassDecl
name = Complex
fields =
- VarDecl
name = Real
type = float
- VarDecl
name = Imag
type = float
^ I want to end up with something like this
edit: Bonus question
Is there also a way to show the name of the parameter..? Like: ClassDecl(name=Complex, fields=List( ... ) ?
Check out a small extensions library named sext. It exports these two functions exactly for purposes like that.
Here's how it can be used for your example:
object Demo extends App {
import sext._
case class ClassDecl( kind : Kind, list : List[ VarDecl ] )
sealed trait Kind
case object Complex extends Kind
case class VarDecl( a : Int, b : String )
val data = ClassDecl(Complex,List(VarDecl(1, "abcd"), VarDecl(2, "efgh")))
println("treeString output:\n")
println(data.treeString)
println()
println("valueTreeString output:\n")
println(data.valueTreeString)
}
Following is the output of this program:
treeString output:
ClassDecl:
- Complex
- List:
| - VarDecl:
| | - 1
| | - abcd
| - VarDecl:
| | - 2
| | - efgh
valueTreeString output:
- kind:
- list:
| - - a:
| | | 1
| | - b:
| | | abcd
| - - a:
| | | 2
| | - b:
| | | efgh
Starting Scala 2.13, case classes (which are an implementation of Product) are now provided with a productElementNames method which returns an iterator over their field's names.
Combined with Product::productIterator which provides the values of a case class, we have a simple way to pretty print case classes without requiring reflection:
def pprint(obj: Any, depth: Int = 0, paramName: Option[String] = None): Unit = {
val indent = " " * depth
val prettyName = paramName.fold("")(x => s"$x: ")
val ptype = obj match { case _: Iterable[Any] => "" case obj: Product => obj.productPrefix case _ => obj.toString }
println(s"$indent$prettyName$ptype")
obj match {
case seq: Iterable[Any] =>
seq.foreach(pprint(_, depth + 1))
case obj: Product =>
(obj.productIterator zip obj.productElementNames)
.foreach { case (subObj, paramName) => pprint(subObj, depth + 1, Some(paramName)) }
case _ =>
}
}
which for your specific scenario:
// sealed trait Kind
// case object Complex extends Kind
// case class VarDecl(a: Int, b: String)
// case class ClassDecl(kind: Kind, decls: List[VarDecl])
val data = ClassDecl(Complex, List(VarDecl(1, "abcd"), VarDecl(2, "efgh")))
pprint(data)
produces:
ClassDecl
kind: Complex
decls:
VarDecl
a: 1
b: abcd
VarDecl
a: 2
b: efgh
Use the com.lihaoyi.pprint library.
libraryDependencies += "com.lihaoyi" %% "pprint" % "0.4.1"
val data = ...
val str = pprint.tokenize(data).mkString
println(str)
you can also configure width, height, indent and colors:
pprint.tokenize(data, width = 80).mkString
Docs: https://github.com/com-lihaoyi/PPrint
Here's my solution which greatly improves how http://www.lihaoyi.com/PPrint/ handles the case-classes (see https://github.com/lihaoyi/PPrint/issues/4 ).
e.g. it prints this:
for such a usage:
pprint2 = pprint.copy(additionalHandlers = pprintAdditionalHandlers)
case class Author(firstName: String, lastName: String)
case class Book(isbn: String, author: Author)
val b = Book("978-0486282114", Author("first", "last"))
pprint2.pprintln(b)
code:
import pprint.{PPrinter, Tree, Util}
object PPrintUtils {
// in scala 2.13 this would be even simpler/cleaner due to added product.productElementNames
protected def caseClassToMap(cc: Product): Map[String, Any] = {
val fieldValues = cc.productIterator.toSet
val fields = cc.getClass.getDeclaredFields.toSeq
.filterNot(f => f.isSynthetic || java.lang.reflect.Modifier.isStatic(f.getModifiers))
fields.map { f =>
f.setAccessible(true)
f.getName -> f.get(cc)
}.filter { case (k, v) => fieldValues.contains(v) }
.toMap
}
var pprint2: PPrinter = _
protected def pprintAdditionalHandlers: PartialFunction[Any, Tree] = {
case x: Product =>
val className = x.getClass.getName
// see source code for pprint.treeify()
val shouldNotPrettifyCaseClass = x.productArity == 0 || (x.productArity == 2 && Util.isOperator(x.productPrefix)) || className.startsWith(pprint.tuplePrefix) || className == "scala.Some"
if (shouldNotPrettifyCaseClass)
pprint.treeify(x)
else {
val fieldMap = caseClassToMap(x)
pprint.Tree.Apply(
x.productPrefix,
fieldMap.iterator.flatMap { case (k, v) =>
val prettyValue: Tree = pprintAdditionalHandlers.lift(v).getOrElse(pprint2.treeify(v))
Seq(pprint.Tree.Infix(Tree.Literal(k), "=", prettyValue))
}
)
}
}
pprint2 = pprint.copy(additionalHandlers = pprintAdditionalHandlers)
}
// usage
pprint2.println(SomeFancyObjectWithNestedCaseClasses(...))
import java.lang.reflect.Field
...
/**
* Pretty prints case classes with field names.
* Handles sequences and arrays of such values.
* Ideally, one could take the output and paste it into source code and have it compile.
*/
def prettyPrint(a: Any): String = {
// Recursively get all the fields; this will grab vals declared in parents of case classes.
def getFields(cls: Class[_]): List[Field] =
Option(cls.getSuperclass).map(getFields).getOrElse(Nil) ++
cls.getDeclaredFields.toList.filterNot(f =>
f.isSynthetic || java.lang.reflect.Modifier.isStatic(f.getModifiers))
a match {
// Make Strings look similar to their literal form.
case s: String =>
'"' + Seq("\n" -> "\\n", "\r" -> "\\r", "\t" -> "\\t", "\"" -> "\\\"", "\\" -> "\\\\").foldLeft(s) {
case (acc, (c, r)) => acc.replace(c, r) } + '"'
case xs: Seq[_] =>
xs.map(prettyPrint).toString
case xs: Array[_] =>
s"Array(${xs.map(prettyPrint) mkString ", "})"
// This covers case classes.
case p: Product =>
s"${p.productPrefix}(${
(getFields(p.getClass) map { f =>
f setAccessible true
s"${f.getName} = ${prettyPrint(f.get(p))}"
}) mkString ", "
})"
// General objects and primitives end up here.
case q =>
Option(q).map(_.toString).getOrElse("¡null!")
}
}
Just like parser combinators, Scala already contains pretty printer combinators in the standard library. (note: this library is deprecated as of Scala 2.11. A similar pretty printing library is a part of kiama open source project).
You are not saying it plainly in your question if you need the solution that does "reflection" or you'd like to build the printer explicitly. (though your "bonus question" hints you probably want "reflective" solution)
Anyway, in the case you'd like to develop simple pretty printer using plain Scala library, here it is. The following code is REPLable.
case class VarDecl(name: String, `type`: String)
case class ClassDecl(name: String, fields: List[VarDecl])
import scala.text._
import Document._
def varDoc(x: VarDecl) =
nest(4, text("- VarDecl") :/:
group("name = " :: text(x.name)) :/:
group("type = " :: text(x.`type`))
)
def classDoc(x: ClassDecl) = {
val docs = ((empty:Document) /: x.fields) { (d, f) => varDoc(f) :/: d }
nest(2, text("ClassDecl") :/:
group("name = " :: text(x.name)) :/:
group("fields =" :/: docs))
}
def prettyPrint(d: Document) = {
val writer = new java.io.StringWriter
d.format(1, writer)
writer.toString
}
prettyPrint(classDoc(
ClassDecl("Complex", VarDecl("Real","float") :: VarDecl("Imag","float") :: Nil)
))
Bonus question: wrap the printers into type classes for even greater composability.
The nicest, most concise "out-of-the" box experience I've found is with the Kiama pretty printing library. It doesn't print member names without using additional combinators, but with only import org.kiama.output.PrettyPrinter._; pretty(any(data)) you have a great start:
case class ClassDecl( kind : Kind, list : List[ VarDecl ] )
sealed trait Kind
case object Complex extends Kind
case class VarDecl( a : Int, b : String )
val data = ClassDecl(Complex,List(VarDecl(1, "abcd"), VarDecl(2, "efgh")))
import org.kiama.output.PrettyPrinter._
// `w` is the wrapping width. `1` forces wrapping all components.
pretty(any(data), w=1)
Produces:
ClassDecl (
Complex (),
List (
VarDecl (
1,
"abcd"),
VarDecl (
2,
"efgh")))
Note that this is just the most basic example. Kiama PrettyPrinter is an extremely powerful library with a rich set of combinators specifically designed for intelligent spacing, line wrapping, nesting, and grouping. It's very easy to tweak to suit your needs. As of this posting, it's available in SBT with:
libraryDependencies += "com.googlecode.kiama" %% "kiama" % "1.8.0"
Using reflection
import scala.reflect.ClassTag
import scala.reflect.runtime.universe._
object CaseClassBeautifier {
def getCaseAccessors[T: TypeTag] = typeOf[T].members.collect {
case m: MethodSymbol if m.isCaseAccessor => m
}.toList
def nice[T:TypeTag](x: T)(implicit classTag: ClassTag[T]) : String = {
val instance = x.asInstanceOf[T]
val mirror = runtimeMirror(instance.getClass.getClassLoader)
val accessors = getCaseAccessors[T]
var res = List.empty[String]
accessors.foreach { z ⇒
val instanceMirror = mirror.reflect(instance)
val fieldMirror = instanceMirror.reflectField(z.asTerm)
val s = s"${z.name} = ${fieldMirror.get}"
res = s :: res
}
val beautified = x.getClass.getSimpleName + "(" + res.mkString(", ") + ")"
beautified
}
}
This is a shamless copy paste of #F. P Freely, but
I've added an indentation feature
slight modifications so that the output will be of correct Scala style (and will compile for all primative types)
Fixed string literal bug
Added support for java.sql.Timestamp (as I use this with Spark a lot)
Tada!
// Recursively get all the fields; this will grab vals declared in parents of case classes.
def getFields(cls: Class[_]): List[Field] =
Option(cls.getSuperclass).map(getFields).getOrElse(Nil) ++
cls.getDeclaredFields.toList.filterNot(f =>
f.isSynthetic || java.lang.reflect.Modifier.isStatic(f.getModifiers))
// FIXME fix bug where indent seems to increase too much
def prettyfy(a: Any, indentSize: Int = 0): String = {
val indent = List.fill(indentSize)(" ").mkString
val newIndentSize = indentSize + 2
(a match {
// Make Strings look similar to their literal form.
case string: String =>
val conversionMap = Map('\n' -> "\\n", '\r' -> "\\r", '\t' -> "\\t", '\"' -> "\\\"", '\\' -> "\\\\")
string.map(c => conversionMap.getOrElse(c, c)).mkString("\"", "", "\"")
case xs: Seq[_] =>
xs.map(prettyfy(_, newIndentSize)).toString
case xs: Array[_] =>
s"Array(${xs.map(prettyfy(_, newIndentSize)).mkString(", ")})"
case map: Map[_, _] =>
s"Map(\n" + map.map {
case (key, value) => " " + prettyfy(key, newIndentSize) + " -> " + prettyfy(value, newIndentSize)
}.mkString(",\n") + "\n)"
case None => "None"
case Some(x) => "Some(" + prettyfy(x, newIndentSize) + ")"
case timestamp: Timestamp => "new Timestamp(" + timestamp.getTime + "L)"
case p: Product =>
s"${p.productPrefix}(\n${
getFields(p.getClass)
.map { f =>
f.setAccessible(true)
s" ${f.getName} = ${prettyfy(f.get(p), newIndentSize)}"
}
.mkString(",\n")
}\n)"
// General objects and primitives end up here.
case q =>
Option(q).map(_.toString).getOrElse("null")
})
.split("\n", -1).mkString("\n" + indent)
}
E.g.
case class Foo(bar: String, bob: Int)
case class Alice(foo: Foo, opt: Option[String], opt2: Option[String])
scala> prettyPrint(Alice(Foo("hello world", 10), Some("asdf"), None))
res6: String =
Alice(
foo = Foo(
bar = "hello world",
bob = 10
),
opt = Some("asdf"),
opt2 = None
)
If you use Apache Spark, you can use the following method to print your case classes :
def prettyPrint[T <: Product : scala.reflect.runtime.universe.TypeTag](c:T) = {
import play.api.libs.json.Json
println(Json.prettyPrint(Json.parse(Seq(c).toDS().toJSON.head)))
}
This gives a nicely formatted JSON representation of your case class instance. Make sure sparkSession.implicits._ is imported
example:
case class Adress(country:String,city:String,zip:Int,street:String)
case class Person(name:String,age:Int,adress:Adress)
val person = Person("Peter",36,Adress("Switzerland","Zürich",9876,"Bahnhofstrasse 69"))
prettyPrint(person)
gives :
{
"name" : "Peter",
"age" : 36,
"adress" : {
"country" : "Switzerland",
"city" : "Zürich",
"zip" : 9876,
"street" : "Bahnhofstrasse 69"
}
}
I would suggest using the same print that is used in the AssertEquals of your test framework of choice. I was using Scalameta and munit.Assertions.munitPrint(clue: => Any): String does the trick. I can pass nested classes to it and see the whole tree with the proper indentation.

Selection Sort Generic type implementation

I worked my way implementing a recursive version of selection and quick sort,i am trying to modify the code in a way that it can sort a list of any generic type , i want to assume that the generic type supplied can be converted to Comparable at runtime.
Does anyone have a link ,code or tutorial on how to do this please
I am trying to modify this particular code
'def main (args:Array[String]){
val l = List(2,4,5,6,8)
print(quickSort(l))
}
def quickSort(x:List[Int]):List[Int]={
x match{
case xh::xt =>
{
val (first,pivot,second) = partition(x)
quickSort (first):::(pivot :: quickSort(second))
}
case Nil => {x}
}
}
def partition (x:List[Int])=
{
val pivot =x.head
var first:List[Int]=List ()
var second : List[Int]=List ()
val fun=(i:Int)=> {
if (i<pivot)
first=i::first
else
second=i::second
}
x.tail.foreach(fun)
(first,pivot,second)
}
enter code here
def main (args:Array[String]){
val l = List(2,4,5,6,8)
print(quickSort(l))
}
def quickSort(x:List[Int]):List[Int]={
x match{
case xh::xt =>
{
val (first,pivot,second) = partition(x)
quickSort (first):::(pivot :: quickSort(second))
}
case Nil => {x}
}
}
def partition (x:List[Int])=
{
val pivot =x.head
var first:List[Int]=List ()
var second : List[Int]=List ()
val fun=(i:Int)=> {
if (i<pivot)
first=i::first
else
second=i::second
}
x.tail.foreach(fun)
(first,pivot,second)
} '
Language: SCALA
In Scala, Java Comparator is replaced by Ordering (quite similar but comes with more useful methods). They are implemented for several types (primitives, strings, bigDecimals, etc.) and you can provide your own implementations.
You can then use scala implicit to ask the compiler to pick the correct one for you:
def sort[A]( lst: List[A] )( implicit ord: Ordering[A] ) = {
...
}
If you are using a predefined ordering, just call:
sort( myLst )
and the compiler will infer the second argument. If you want to declare your own ordering, use the keyword implicit in the declaration. For instance:
implicit val fooOrdering = new Ordering[Foo] {
def compare( f1: Foo, f2: Foo ) = {...}
}
and it will be implicitly use if you try to sort a List of Foo.
If you have several implementations for the same type, you can also explicitly pass the correct ordering object:
sort( myFooLst )( fooOrdering )
More info in this post.
For Quicksort, I'll modify an example from the "Scala By Example" book to make it more generic.
class Quicksort[A <% Ordered[A]] {
def sort(a:ArraySeq[A]): ArraySeq[A] =
if (a.length < 2) a
else {
val pivot = a(a.length / 2)
sort (a filter (pivot >)) ++ (a filter (pivot == )) ++
sort (a filter(pivot <))
}
}
Test with Int
scala> val quicksort = new Quicksort[Int]
quicksort: Quicksort[Int] = Quicksort#38ceb62f
scala> val a = ArraySeq(5, 3, 2, 2, 1, 1, 9, 39 ,219)
a: scala.collection.mutable.ArraySeq[Int] = ArraySeq(5, 3, 2, 2, 1, 1, 9, 39, 21
9)
scala> quicksort.sort(a).foreach(n=> (print(n), print (" " )))
1 1 2 2 3 5 9 39 219
Test with a custom class implementing Ordered
scala> case class Meh(x: Int, y:Int) extends Ordered[Meh] {
| def compare(that: Meh) = (x + y).compare(that.x + that.y)
| }
defined class Meh
scala> val q2 = new Quicksort[Meh]
q2: Quicksort[Meh] = Quicksort#7677ce29
scala> val a3 = ArraySeq(Meh(1,1), Meh(12,1), Meh(0,1), Meh(2,2))
a3: scala.collection.mutable.ArraySeq[Meh] = ArraySeq(Meh(1,1), Meh(12,1), Meh(0
,1), Meh(2,2))
scala> q2.sort(a3)
res7: scala.collection.mutable.ArraySeq[Meh] = ArraySeq(Meh(0,1), Meh(1,1), Meh(
2,2), Meh(12,1))
Even though, when coding Scala, I'm used to prefer functional programming style (via combinators or recursion) over imperative style (via variables and iterations), THIS TIME, for this specific problem, old school imperative nested loops result in simpler code for the reader. I don't think falling back to imperative style is a mistake for certain classes of problems (such as sorting algorithms which usually transform the input buffer (like a procedure) rather than resulting to a new sorted one
Here it is my solution:
package bitspoke.algo
import scala.math.Ordered
import scala.collection.mutable.Buffer
abstract class Sorter[T <% Ordered[T]] {
// algorithm provided by subclasses
def sort(buffer : Buffer[T]) : Unit
// check if the buffer is sorted
def sorted(buffer : Buffer[T]) = buffer.isEmpty || buffer.view.zip(buffer.tail).forall { t => t._2 > t._1 }
// swap elements in buffer
def swap(buffer : Buffer[T], i:Int, j:Int) {
val temp = buffer(i)
buffer(i) = buffer(j)
buffer(j) = temp
}
}
class SelectionSorter[T <% Ordered[T]] extends Sorter[T] {
def sort(buffer : Buffer[T]) : Unit = {
for (i <- 0 until buffer.length) {
var min = i
for (j <- i until buffer.length) {
if (buffer(j) < buffer(min))
min = j
}
swap(buffer, i, min)
}
}
}
As you can see, rather than using java.lang.Comparable, I preferred scala.math.Ordered and Scala View Bounds rather than Upper Bounds. That's certainly works thanks to many Scala Implicit Conversions of primitive types to Rich Wrappers.
You can write a client program as follows:
import bitspoke.algo._
import scala.collection.mutable._
val sorter = new SelectionSorter[Int]
val buffer = ArrayBuffer(3, 0, 4, 2, 1)
sorter.sort(buffer)
assert(sorter.sorted(buffer))