I have implemented a recursive method to check if number of parenthesis in a string is valid or not. Here is the code
def balance(chars: List[Char]): Boolean = {
#tailrec
def isValid(newChars: List[Char], difference: Int): Boolean = {
if (newChars.isEmpty) difference == 0
else if (difference < 0) false
else {
var newDifference = difference // Scala IDE gives warning here
if (newChars.head == '(') newDifference = difference + 1
else if (newChars.head == ')') newDifference = difference - 1
isValid(newChars.tail, newDifference)
}
}
isValid(chars, 0)
}
I tested the above code for the following test cases and it works fine So I am only looking for improving the if/else ladder.
println("Testing parenthesis balancing")
assert(balance("(Sachin is learning (scala) and (spark))".toList))
assert(!balance("(Invalid))(expression)".toList))
assert(balance("".toList))
assert(balance("()()".toList))
assert(!balance("{())}{()}".toList))
As mentioned in the code, Scala IDE complains on that line saying
Avoid mutable local variables
I am not really sure how to compute the value of newDifference without using if/else. Other option I could see is directly call isValid method in if/else ladder with computed values of newDifference.
I am still learning Scala So I want to know what could be the best possible way to write this code without mutating the local variable (or any other warning).
People use pattern match for that. That way you can avoid both mutable variables and the "if/else ladder", that makes for horrible "spaghetti code".
def isValid(chars: List[Char], ps: Int = 0) = (chars, ps) match {
case (Nil, _) => ps == 0
case (_, _) if ps < 0 => false
case ('(' :: tail, ps) => isValid(tail, ps + 1)
case (')' :: tail, ps) => isValid(tail, ps - 1)
case (_ :: tail, ps) => isValid(tail, ps)
}
You can write:
val newDifference =
if (newChars.head == '(') difference + 1
else if (newChars.head == ')') difference - 1
else difference;
as if in Scala is an expression, or use match, which would be considered more idiomatic in this case:
val newDifference = newChars.head match {
case '(' => difference + 1
case ')' => difference - 1
case _ => difference
}
The whole function can be converted into a single match on newChars, but I'll leave that to you. See the first example here for some ideas.
Related
I am running a code to balance brackets in statement. I think i have gotten it correct but it is failing on one particular statement, i need to understand why?
This is the test in particular it is failing "())("
More than the coding i think i need to fix the algo, any pointers?
def balance(chars: List[Char]): Boolean = {
def find(c: Char, l: List[Char], i: Int): Int={
if( l.isEmpty ) {
if(c=='(')
i+1
else if(c==')')
i-1
else
i
}
else if (c=='(')
find(l.head, l.tail, i+1)
else if(c==')')
find(l.head,l.tail, i-1)
else
find(l.head,l.tail, i)
}
if(find(chars.head, chars.tail,0) ==0 )
true
else
false
}
balance("())(".toList) //passes when it should fail
balance(":-)".toList)
balance("(if (zero? x) max (/ 1 x))".toList)
balance("I told him (that it's not (yet) done).\n(But he wasn't listening)".toList)
Here is a version:
def balance(chars: List[Char]): Boolean = {
def inner(c: List[Char], count: Int): Boolean = c match {
case Nil => count == 0 // Line 1
case ')' :: _ if count < 1 => false // Line 2
case ')' :: xs => inner(xs, count - 1) // Line 3
case '(' :: xs => inner(xs, count + 1) // Line 4
case _ :: xs => inner(xs, count) // Line 5
}
inner(chars, 0)
}
So in your code, I think you are missing the additional check for count < 1 when you encounter the right paranthesis! So you need an additional else if that checks for both the ')' and count < 1 (Line 2 in the example code above)
Using map:
def balance(chars: List[Char]): Boolean = {
chars.map(c =>
c match {
case '(' => 1
case ')' => -1
case _ => 0
}
).scanLeft(0)(_ + _).dropWhile(_ >= 0).isEmpty
}
You've made a very simple and completely understandable mistake. The parentheses in )( are balanced, by your current definition. It's just that they're not balanced in the way we would usually think. After the first character, you have -1 unclosed parentheses, and then after the second characte we're back to 0, so everything is fine. If the parenthesis count ever drops below zero, the parentheses cannot possibly be balanced.
Now there are two real ways to handle this. The quick and dirty solution is to throw an exception.
case object UnbalancedException extends Exception
if (i < 0)
throw UnbalancedException
then catch it and return false in balance.
try {
... // find() call goes in here
} catch {
case UnbalancedException => false
}
The more functional solution would be to have find return an Option[Int]. During the recursion, if you ever get a None result, then return None. Otherwise, behave as normally and return Some(n). If you ever encounter the case where i < 0 then return None to indicate failure. Then in balance, if the result is nonzero or the result is None, return false. This can be made prettier with for notation, but if you're just starting out then it can be very helpful to write it out by hand.
You can also use the property of Stack data structure to solve this problem. When you see open bracket, you push it into the stack. When you see close bracket, you pop from the stack (instead of Stack I'm using List, because immutable Stack is deprecated in Scala):
def isBalanced(chars: Seq[Char]): Boolean = {
import scala.annotation.tailrec
case class BracketInfo(c: Char, idx: Int)
def isOpen(c: Char): Boolean = c == '('
def isClose(c: Char): Boolean = c == ')'
def safePop[T](stack: List[T]): Option[T] = {
if (stack.length <= 1) stack.headOption
else stack.tail.headOption
}
#tailrec
def isBalanced(chars: Seq[Char], idx: Int, stack: List[BracketInfo]): Boolean = {
chars match {
case Seq(c, tail#_*) =>
val newStack = BracketInfo(c, idx) :: stack // Stack.push
if (isOpen(c)) isBalanced(tail, idx + 1, newStack)
else if (isClose(c)) {
safePop(stack) match {
case Some(b) => isBalanced(tail, idx + 1, stack.tail)
case None =>
println(s"Closed bracket '$c' at index $idx was not opened")
false
}
}
else isBalanced(tail, idx + 1, stack)
case Seq() =>
if (stack.nonEmpty) {
println("Stack is not empty => there are non-closed brackets at positions: ")
println(s"${stack.map(_.idx).mkString(" ")}")
}
stack.isEmpty
}
}
isBalanced(chars, 0, List.empty[BracketInfo])
}
I was trying my hand at writing an IP generator given a string of numbers. The generator would take as an input a string of number such as "17234" and will return all possible list of ips as follows:
1.7.2.34
1.7.23.4
1.72.3.4
17.2.3.4
I attempted to write a snippet to do the generation as follows:
def genip(ip:String):Unit = {
def legal(ip:String):Boolean = (ip.size == 1) || (ip.size == 2) || (ip.size == 3)
def genips(ip:String,portion:Int,accum:String):Unit = portion match {
case 1 if legal(ip) => println(accum+ip)
case _ if portion > 1 => {
genips(ip.drop(1),portion-1,if(accum.size == 0) ip.take(1)+"." else accum+ip.take(1)+".")
genips(ip.drop(2),portion-1,if(accum.size == 0) ip.take(2)+"." else accum+ip.take(2)+".")
genips(ip.drop(3),portion-1,if(accum.size == 0) ip.take(3)+"." else accum+ip.take(3)+".")
}
case _ => return
}
genips(ip,4,"")
}
The idea is to partition the string into four octets and then further partition the octet into strings of size "1","2" and "3" and then recursively descend into the remaining string.
I am not sure if I am on the right track but it would be great if somebody could suggest a more functional way of accomplishing the same.
Thanks
Here is an alternative version of the attached code:
def generateIPs(digits : String) : Seq[String] = generateIPs(digits, 4)
private def generateIPs(digits : String, partsLeft : Int) : Seq[String] = {
if ( digits.size < partsLeft || digits.size > partsLeft * 3) {
Nil
} else if(partsLeft == 1) {
Seq(digits)
} else {
(1 to 3).map(n => generateIPs(digits.drop(n), partsLeft - 1)
.map(digits.take(n) + "." + _)
).flatten
}
}
println("Results:\n" + generateIPs("17234").mkString("\n"))
Major changes:
Methods now return the collection of strings (rather than Unit), so they are proper functions (rather than working of side effects) and can be easily tested;
Avoiding repeating the same code 3 times depending on the size of the bunch of numbers we take;
Not passing accumulated interim result as a method parameter - in this case it doesn't have sense since you'll have at most 4 recursive calls and it's easier to read without it, though as you're loosing the tail recursion in many case it might be reasonable to leave it.
Note: The last map statement is a good candidate to be replaced by for comprehension, which many developers find easier to read and reason about, though I will leave it as an exercise :)
You code is the right idea; I'm not sure making it functional really helps anything, but I'll show both functional and side-effecting ways to do what you want. First, we'd like a good routine to chunk off some of the numbers, making sure an okay number are left for the rest of the chunking, and making sure they're in range for IPs:
def validSize(i: Int, len: Int, more: Int) = i + more <= len && i + 3*more >= len
def chunk(s: String, more: Int) = {
val parts = for (i <- 1 to 3 if validSize(i, s.length, more)) yield s.splitAt(i)
parts.filter(_._1.toInt < 256)
}
Now we need to use chunk recursively four times to generate the possibilities. Here's a solution that is mutable internally and iterative:
def genIPs(digits: String) = {
var parts = List(("", digits))
for (i <- 1 to 4) {
parts = parts.flatMap{ case (pre, post) =>
chunk(post, 4-i).map{ case (x,y) => (pre+x+".", y) }
}
}
parts.map(_._1.dropRight(1))
}
Here's one that recurses using Iterator:
def genIPs(digits: String) = Iterator.iterate(List((3,"",digits))){ _.flatMap{
case(j, pre, post) => chunk(post, j).map{ case(x,y) => (j-1, pre+x+".", y) }
}}.dropWhile(_.head._1 >= 0).next.map(_._2.dropRight(1))
The logic is the same either way. Here it is working:
scala> genIPs("1238516")
res2: List[String] = List(1.23.85.16, 1.238.5.16, 1.238.51.6,
12.3.85.16, 12.38.5.16, 12.38.51.6,
123.8.5.16, 123.8.51.6, 123.85.1.6)
Scenario:
val col: IndexedSeq[Array[Char]] = for (i <- 1 to n) yield {
val x = for (j <- 1 to m) yield 'x'
x.toArray
}
This is a fairly simple char matrix. toArray used to allow updating.
var west = last.x - 1
while (west >= 0 && arr(last.y)(west) == '.') {
arr(last.y)(west) = ch;
west -= 1;
}
This is updating all . to ch until a non-dot char is found.
Generically, update until stop condition is met, unknown number of steps.
What is the idiomatic equivalent of it?
Conclusion
It's doable, but the trade-off isn't worth it, a lot of performance is lost to expressive syntax when the collection allows updating.
Your wish for a "cleaner, more idiomatic" solution is of course a little fuzzy, because it leaves a lot of room for subjectivity. In general, I'd consider a tail-recursive updating routine more idiomatic, but it might not be "cleaner" if you're more familiar with a non-functional programming style. I came up with this:
#tailrec
def update(arr:List[Char], replace:Char, replacement:Char, result:List[Char] = Nil):List[Char] = arr match {
case `replace` :: tail =>
update(tail, replace, replacement, replacement :: result)
case _ => result.reverse ::: arr
}
This takes one of the inner sequences (assuming a List for easier pattern matching, since Arrays are trivially convertible to lists), and replaces the replace char with the replacement recursively.
You can then use map to update the outer sequence, like so:
col.map { x => update(x, '.', ch) }
Another more reusable alternative is writing your own mapUntil, or using one which is implemented in a supplemental library (Scalaz probably has something like it). The one I came up with looks like this:
def mapUntil[T](input:List[T])(f:(T => Option[T])) = {
#tailrec
def inner(xs:List[T], result:List[T]):List[T] = xs match {
case Nil => Nil
case head :: tail => f(head) match {
case None => (head :: result).reverse ::: tail
case Some(x) => inner(tail, x :: result)
}
}
inner(input, Nil)
}
It does the same as a regular map invocation, except that it stops as soon as the passed function returns None, e.g.
mapUntil(List(1,2,3,4)) {
case x if x >= 3 => None
case x => Some(x-1)
}
Will result in
List[Int] = List(0, 1, 3, 4)
If you want to look at Scalaz, this answer might be a good place to start.
x3ro's answer is the right answer, esp. if you care about performance or are going to be using this operation in multiple places. I would like to add simple solution using only what you find in the collections API:
col.map { a =>
val (l, r) = a.span(_ == '.')
l.map {
case '.' => ch
case x => x
} ++ r
}
What's the best way to terminate a fold early? As a simplified example, imagine I want to sum up the numbers in an Iterable, but if I encounter something I'm not expecting (say an odd number) I might want to terminate. This is a first approximation
def sumEvenNumbers(nums: Iterable[Int]): Option[Int] = {
nums.foldLeft (Some(0): Option[Int]) {
case (Some(s), n) if n % 2 == 0 => Some(s + n)
case _ => None
}
}
However, this solution is pretty ugly (as in, if I did a .foreach and a return -- it'd be much cleaner and clearer) and worst of all, it traverses the entire iterable even if it encounters a non-even number.
So what would be the best way to write a fold like this, that terminates early? Should I just go and write this recursively, or is there a more accepted way?
My first choice would usually be to use recursion. It is only moderately less compact, is potentially faster (certainly no slower), and in early termination can make the logic more clear. In this case you need nested defs which is a little awkward:
def sumEvenNumbers(nums: Iterable[Int]) = {
def sumEven(it: Iterator[Int], n: Int): Option[Int] = {
if (it.hasNext) {
val x = it.next
if ((x % 2) == 0) sumEven(it, n+x) else None
}
else Some(n)
}
sumEven(nums.iterator, 0)
}
My second choice would be to use return, as it keeps everything else intact and you only need to wrap the fold in a def so you have something to return from--in this case, you already have a method, so:
def sumEvenNumbers(nums: Iterable[Int]): Option[Int] = {
Some(nums.foldLeft(0){ (n,x) =>
if ((n % 2) != 0) return None
n+x
})
}
which in this particular case is a lot more compact than recursion (though we got especially unlucky with recursion since we had to do an iterable/iterator transformation). The jumpy control flow is something to avoid when all else is equal, but here it's not. No harm in using it in cases where it's valuable.
If I was doing this often and wanted it within the middle of a method somewhere (so I couldn't just use return), I would probably use exception-handling to generate non-local control flow. That is, after all, what it is good at, and error handling is not the only time it's useful. The only trick is to avoid generating a stack trace (which is really slow), and that's easy because the trait NoStackTrace and its child trait ControlThrowable already do that for you. Scala already uses this internally (in fact, that's how it implements the return from inside the fold!). Let's make our own (can't be nested, though one could fix that):
import scala.util.control.ControlThrowable
case class Returned[A](value: A) extends ControlThrowable {}
def shortcut[A](a: => A) = try { a } catch { case Returned(v) => v }
def sumEvenNumbers(nums: Iterable[Int]) = shortcut{
Option(nums.foldLeft(0){ (n,x) =>
if ((x % 2) != 0) throw Returned(None)
n+x
})
}
Here of course using return is better, but note that you could put shortcut anywhere, not just wrapping an entire method.
Next in line for me would be to re-implement fold (either myself or to find a library that does it) so that it could signal early termination. The two natural ways of doing this are to not propagate the value but an Option containing the value, where None signifies termination; or to use a second indicator function that signals completion. The Scalaz lazy fold shown by Kim Stebel already covers the first case, so I'll show the second (with a mutable implementation):
def foldOrFail[A,B](it: Iterable[A])(zero: B)(fail: A => Boolean)(f: (B,A) => B): Option[B] = {
val ii = it.iterator
var b = zero
while (ii.hasNext) {
val x = ii.next
if (fail(x)) return None
b = f(b,x)
}
Some(b)
}
def sumEvenNumbers(nums: Iterable[Int]) = foldOrFail(nums)(0)(_ % 2 != 0)(_ + _)
(Whether you implement the termination by recursion, return, laziness, etc. is up to you.)
I think that covers the main reasonable variants; there are some other options also, but I'm not sure why one would use them in this case. (Iterator itself would work well if it had a findOrPrevious, but it doesn't, and the extra work it takes to do that by hand makes it a silly option to use here.)
The scenario you describe (exit upon some unwanted condition) seems like a good use case for the takeWhile method. It is essentially filter, but should end upon encountering an element that doesn't meet the condition.
For example:
val list = List(2,4,6,8,6,4,2,5,3,2)
list.takeWhile(_ % 2 == 0) //result is List(2,4,6,8,6,4,2)
This will work just fine for Iterators/Iterables too. The solution I suggest for your "sum of even numbers, but break on odd" is:
list.iterator.takeWhile(_ % 2 == 0).foldLeft(...)
And just to prove that it's not wasting your time once it hits an odd number...
scala> val list = List(2,4,5,6,8)
list: List[Int] = List(2, 4, 5, 6, 8)
scala> def condition(i: Int) = {
| println("processing " + i)
| i % 2 == 0
| }
condition: (i: Int)Boolean
scala> list.iterator.takeWhile(condition _).sum
processing 2
processing 4
processing 5
res4: Int = 6
You can do what you want in a functional style using the lazy version of foldRight in scalaz. For a more in depth explanation, see this blog post. While this solution uses a Stream, you can convert an Iterable into a Stream efficiently with iterable.toStream.
import scalaz._
import Scalaz._
val str = Stream(2,1,2,2,2,2,2,2,2)
var i = 0 //only here for testing
val r = str.foldr(Some(0):Option[Int])((n,s) => {
println(i)
i+=1
if (n % 2 == 0) s.map(n+) else None
})
This only prints
0
1
which clearly shows that the anonymous function is only called twice (i.e. until it encounters the odd number). That is due to the definition of foldr, whose signature (in case of Stream) is def foldr[B](b: B)(f: (Int, => B) => B)(implicit r: scalaz.Foldable[Stream]): B. Note that the anonymous function takes a by name parameter as its second argument, so it need no be evaluated.
Btw, you can still write this with the OP's pattern matching solution, but I find if/else and map more elegant.
Well, Scala does allow non local returns. There are differing opinions on whether or not this is a good style.
scala> def sumEvenNumbers(nums: Iterable[Int]): Option[Int] = {
| nums.foldLeft (Some(0): Option[Int]) {
| case (None, _) => return None
| case (Some(s), n) if n % 2 == 0 => Some(s + n)
| case (Some(_), _) => None
| }
| }
sumEvenNumbers: (nums: Iterable[Int])Option[Int]
scala> sumEvenNumbers(2 to 10)
res8: Option[Int] = None
scala> sumEvenNumbers(2 to 10 by 2)
res9: Option[Int] = Some(30)
EDIT:
In this particular case, as #Arjan suggested, you can also do:
def sumEvenNumbers(nums: Iterable[Int]): Option[Int] = {
nums.foldLeft (Some(0): Option[Int]) {
case (Some(s), n) if n % 2 == 0 => Some(s + n)
case _ => return None
}
}
You can use foldM from cats lib (as suggested by #Didac) but I suggest to use Either instead of Option if you want to get actual sum out.
bifoldMap is used to extract the result from Either.
import cats.implicits._
def sumEven(nums: Stream[Int]): Either[Int, Int] = {
nums.foldM(0) {
case (acc, n) if n % 2 == 0 => Either.right(acc + n)
case (acc, n) => {
println(s"Stopping on number: $n")
Either.left(acc)
}
}
}
examples:
println("Result: " + sumEven(Stream(2, 2, 3, 11)).bifoldMap(identity, identity))
> Stopping on number: 3
> Result: 4
println("Result: " + sumEven(Stream(2, 7, 2, 3)).bifoldMap(identity, identity))
> Stopping on number: 7
> Result: 2
Cats has a method called foldM which does short-circuiting (for Vector, List, Stream, ...).
It works as follows:
def sumEvenNumbers(nums: Stream[Int]): Option[Long] = {
import cats.implicits._
nums.foldM(0L) {
case (acc, c) if c % 2 == 0 => Some(acc + c)
case _ => None
}
}
If it finds a not even element it returns None without computing the rest, otherwise it returns the sum of the even entries.
If you want to keep count until an even entry is found, you should use an Either[Long, Long]
#Rex Kerr your answer helped me, but I needed to tweak it to use Either
def foldOrFail[A,B,C,D](map: B => Either[D, C])(merge: (A, C) => A)(initial: A)(it: Iterable[B]): Either[D, A] = {
val ii= it.iterator
var b= initial
while (ii.hasNext) {
val x= ii.next
map(x) match {
case Left(error) => return Left(error)
case Right(d) => b= merge(b, d)
}
}
Right(b)
}
You could try using a temporary var and using takeWhile. Here is a version.
var continue = true
// sample stream of 2's and then a stream of 3's.
val evenSum = (Stream.fill(10)(2) ++ Stream.fill(10)(3)).takeWhile(_ => continue)
.foldLeft(Option[Int](0)){
case (result,i) if i%2 != 0 =>
continue = false;
// return whatever is appropriate either the accumulated sum or None.
result
case (optionSum,i) => optionSum.map( _ + i)
}
The evenSum should be Some(20) in this case.
You can throw a well-chosen exception upon encountering your termination criterion, handling it in the calling code.
A more beutiful solution would be using span:
val (l, r) = numbers.span(_ % 2 == 0)
if(r.isEmpty) Some(l.sum)
else None
... but it traverses the list two times if all the numbers are even
Just for an "academic" reasons (:
var headers = Source.fromFile(file).getLines().next().split(",")
var closeHeaderIdx = headers.takeWhile { s => !"Close".equals(s) }.foldLeft(0)((i, S) => i+1)
Takes twice then it should but it is a nice one liner.
If "Close" not found it will return
headers.size
Another (better) is this one:
var headers = Source.fromFile(file).getLines().next().split(",").toList
var closeHeaderIdx = headers.indexOf("Close")
How can I refactor this code in functional style (scala idiomatic)
def findFirst[T](objects: List[T]):T = {
for (obj <- objects) {
if (expensiveFunc(obj) != null) return obj
}
null.asInstanceOf[T]
}
This is almost exactly what the find method does, except that it returns an Option. So if you want this exact behavior, you can add a call to Option.orNull, like this:
objects.find(expensiveFunc).orNull
First, don't use null in Scala (except when interacting with Java code) but Options. Second, replace loops with recursion. Third, have a look at the rich API of Scala functions, the method you are looking for already exists as pointed by sepp2k.
For learning puprose your example could be rewritten as:
def findFirst[T](objects: List[T]):Option[T] = objects match {
case first :: rest if expensiveFunc( first ) != null => Some( first )
case _ :: rest => findFirst( rest )
case Nil => None
}
How about a fold?
Our somehow pseudo-expensive function:
scala> def divByFive (n: Int) : Option[Int] = {
| println ("processing " + n)
| if (n % 5 == 0) Some (n) else None }
divByFive: (n: Int)Option[Int]
Folding on an Option:
scala> ((None: Option[Int]) /: (1 to 11)) ((a, b) =>
| if (a != None) a else divByFive (b))
processing 1
processing 2
processing 3
processing 4
processing 5
res69: Option[Int] = Some(5)