Scala foldLeft while some conditions are true - scala

How to emulate following behavior in Scala? i.e. keep folding while some certain conditions on the accumulator are met.
def foldLeftWhile[B](z: B, p: B => Boolean)(op: (B, A) => B): B
For example
scala> val seq = Seq(1, 2, 3, 4)
seq: Seq[Int] = List(1, 2, 3, 4)
scala> seq.foldLeftWhile(0, _ < 3) { (acc, e) => acc + e }
res0: Int = 1
scala> seq.foldLeftWhile(0, _ < 7) { (acc, e) => acc + e }
res1: Int = 6
UPDATES:
Based on #Dima answer, I realized that my intention was a little bit side-effectful. So I made it synchronized with takeWhile, i.e. there would be no advancement if the predicate does not match. And add some more examples to make it clearer. (Note: that will not work with Iterators)

First, note that your example seems wrong. If I understand correctly what you describe, the result should be 1 (the last value on which the predicate _ < 3 was satisfied), not 6
The simplest way to do this is using a return statement, which is very frowned upon in scala, but I thought, I'd mention it for the sake of completeness.
def foldLeftWhile[A, B](seq: Seq[A], z: B, p: B => Boolean)(op: (B, A) => B): B = foldLeft(z) { case (b, a) =>
val result = op(b, a)
if(!p(result)) return b
result
}
Since we want to avoid using return, scanLeft might be a possibility:
seq.toStream.scanLeft(z)(op).takeWhile(p).last
This is a little wasteful, because it accumulates all (matching) results.
You could use iterator instead of toStream to avoid that, but Iterator does not have .last for some reason, so, you'd have to scan through it an extra time explicitly:
seq.iterator.scanLeft(z)(op).takeWhile(p).foldLeft(z) { case (_, b) => b }

It is pretty straightforward to define what you want in scala. You can define an implicit class which will add your function to any TraversableOnce (that includes Seq).
implicit class FoldLeftWhile[A](trav: TraversableOnce[A]) {
def foldLeftWhile[B](init: B)(where: B => Boolean)(op: (B, A) => B): B = {
trav.foldLeft(init)((acc, next) => if (where(acc)) op(acc, next) else acc)
}
}
Seq(1,2,3,4).foldLeftWhile(0)(_ < 3)((acc, e) => acc + e)
Update, since the question was modified:
implicit class FoldLeftWhile[A](trav: TraversableOnce[A]) {
def foldLeftWhile[B](init: B)(where: B => Boolean)(op: (B, A) => B): B = {
trav.foldLeft((init, false))((a,b) => if (a._2) a else {
val r = op(a._1, b)
if (where(r)) (op(a._1, b), false) else (a._1, true)
})._1
}
}
Note that I split your (z: B, p: B => Boolean) into two higher-order functions. That's just a personal scala style preference.

What about this:
def foldLeftWhile[A, B](z: B, xs: Seq[A], p: B => Boolean)(op: (B, A) => B): B = {
def go(acc: B, l: Seq[A]): B = l match {
case h +: t =>
val nacc = op(acc, h)
if(p(nacc)) go(op(nacc, h), t) else nacc
case _ => acc
}
go(z, xs)
}
val a = Seq(1,2,3,4,5,6)
val r = foldLeftWhile(0, a, (x: Int) => x <= 3)(_ + _)
println(s"$r")
Iterate recursively on the collection while the predicate is true, and then return the accumulator.
You cand try it on scalafiddle

After a while I received a lot of good looking answers. So, I combined them to this single post
a very concise solution by #Dima
implicit class FoldLeftWhile[A](seq: Seq[A]) {
def foldLeftWhile[B](z: B)(p: B => Boolean)(op: (B, A) => B): B = {
seq.toStream.scanLeft(z)(op).takeWhile(p).lastOption.getOrElse(z)
}
}
by #ElBaulP (I modified a little bit to match comment by #Dima)
implicit class FoldLeftWhile[A](seq: Seq[A]) {
def foldLeftWhile[B](z: B)(p: B => Boolean)(op: (B, A) => B): B = {
#tailrec
def foldLeftInternal(acc: B, seq: Seq[A]): B = seq match {
case x :: _ =>
val newAcc = op(acc, x)
if (p(newAcc))
foldLeftInternal(newAcc, seq.tail)
else
acc
case _ => acc
}
foldLeftInternal(z, seq)
}
}
Answer by me (involving side effects)
implicit class FoldLeftWhile[A](seq: Seq[A]) {
def foldLeftWhile[B](z: B)(p: B => Boolean)(op: (B, A) => B): B = {
var accumulator = z
seq
.map { e =>
accumulator = op(accumulator, e)
accumulator -> e
}
.takeWhile { case (acc, _) =>
p(acc)
}
.lastOption
.map { case (acc, _) =>
acc
}
.getOrElse(z)
}
}

Fist exemple: predicate for each element
First you can use inner tail recursive function
implicit class TravExt[A](seq: TraversableOnce[A]) {
def foldLeftWhile[B](z: B, f: A => Boolean)(op: (A, B) => B): B = {
#tailrec
def rec(trav: TraversableOnce[A], z: B): B = trav match {
case head :: tail if f(head) => rec(tail, op(head, z))
case _ => z
}
rec(seq, z)
}
}
Or short version
implicit class TravExt[A](seq: TraversableOnce[A]) {
#tailrec
final def foldLeftWhile[B](z: B, f: A => Boolean)(op: (A, B) => B): B = seq match {
case head :: tail if f(head) => tail.foldLeftWhile(op(head, z), f)(op)
case _ => z
}
}
Then use it
val a = List(1, 2, 3, 4, 5, 6).foldLeftWhile(0, _ < 3)(_ + _)
//a == 3
Second example: for accumulator value:
implicit class TravExt[A](seq: TraversableOnce[A]) {
def foldLeftWhile[B](z: B, f: A => Boolean)(op: (A, B) => B): B = {
#tailrec
def rec(trav: TraversableOnce[A], z: B): B = trav match {
case _ if !f(z) => z
case head :: tail => rec(tail, op(head, z))
case _ => z
}
rec(seq, z)
}
}
Or short version
implicit class TravExt[A](seq: TraversableOnce[A]) {
#tailrec
final def foldLeftWhile[B](z: B, f: A => Boolean)(op: (A, B) => B): B = seq match {
case _ if !f(z) => z
case head :: tail => tail.foldLeftWhile(op(head, z), f)(op)
case _ => z
}
}

Simply use a branch condition on the accumulator:
seq.foldLeft(0, _ < 3) { (acc, e) => if (acc < 3) acc + e else acc}
However you will run every entry of the sequence.

Related

Inline function ambiguity in Scala

When passing an operator lifted to be a function to one of defined higher order functions, Scala allows for very concise syntax, e.g (please ignore the fact that it can be simplified to .product()):
List(1,2,3).fold(1)(_ * _)
To the above I can just pass _ \* _
However having defined my own toy function zipWith(), I need to be very explicit when passing a function:
implicit class EnrichedList[A](val self: List[A]) extends AnyVal {
def zipWith[B, C](that: List[B])
(implicit zipper: A => B => C): List[C] = {
def zipWithHelper(zipper: A => B => C)
(as: List[A])
(bs: List[B]): List[C] = {
(as, bs) match {
case (_, Nil) => Nil
case (Nil, _) => Nil
case (a :: restOfA, b :: restOfB) =>
zipper(a)(b) :: zipWithHelper(zipper)(restOfA)(restOfB)
}
}
zipWithHelper(zipper)(self)(that)
}
}
This: List(1, 3, 4).zipWith(List(3, 4, 5))(_ * _) will not work, saying
Error:(60, 46) missing parameter type for expanded function ((x$1: , x$2) => x$1.$times(x$2))
List(1, 3, 4).zipWith(List(3, 4, 5))(_ * _)
I need to say what type of arguments function takes:
List(1, 3, 4).zipWith(List(3, 4, 5))((x: Int) => (y: Int) => x * y)
Why won't the compiler allow me just to pass in a shorthand version _ * _?
The expression _ * _ is not shorthand for (x: Int) => (y: Int) => x * y. It's a shorthand for (x: Int, y: Int) => x * y. If you change the type of zipper to (A, B) => C instead of A => B => C, it should work. Currying is a thing, it's not just a fancy name for an identity function.
This here compiles:
implicit class EnrichedList[A](val self: List[A]) {
def zipWith[B, C](that: List[B])
(implicit zipper: (A, B) => C): List[C] = {
def zipWithHelper(zipper: (A, B) => C)
(as: List[A])
(bs: List[B]): List[C] = {
(as, bs) match {
case (_, Nil) => Nil
case (Nil, _) => Nil
case (a :: restOfA, b :: restOfB) =>
zipper(a, b) :: zipWithHelper(zipper)(restOfA)(restOfB)
}
}
zipWithHelper(zipper)(self)(that)
}
}
println( List(1, 3, 4).zipWith(List(3, 4, 5))(_ * _) )
and prints
List(3, 12, 20)

Scala cats trampoline

The test("ok") is copied from book "scala with cats" by Noel Welsh and Dave Gurnell pag.254 ("D.4 Safer Folding using Eval
"), the code run fine, it's the trampolined foldRight
import cats.Eval
test("ok") {
val list = (1 to 100000).toList
def foldRightEval[A, B](as: List[A], acc: Eval[B])(fn: (A, Eval[B]) => Eval[B]): Eval[B] =
as match {
case head :: tail =>
Eval.defer(fn(head, foldRightEval(tail, acc)(fn)))
case Nil =>
acc
}
def foldRight[A, B](as: List[A], acc: B)(fn: (A, B) => B): B =
foldRightEval(as, Eval.now(acc)) { (a, b) =>
b.map(fn(a, _))
}.value
val res = foldRight(list, 0L)(_ + _)
assert(res == 5000050000l)
}
The test("ko") returns same values of test("ok") for small list but for long list the value is different. Why?
test("ko") {
val list = (1 to 100000).toList
def foldRightSafer[A, B](as: List[A], acc: B)(fn: (A, B) => B): Eval[B] = as match {
case head :: tail =>
Eval.defer(foldRightSafer(tail, acc)(fn)).map(fn(head, _))
case Nil => Eval.now(acc)
}
val res = foldRightSafer(list, 0)((a, b) => a + b).value
assert(res == 5000050000l)
}
This is #OlegPyzhcov's comment, converted into a community wiki answer
You forgot the L in 0L passed as second argument to foldRightSafer.
Because of that, the inferred generic types of the invocation are
foldRightSafer[Int, Int]((list : List[Int]), (0: Int))((_: Int) + (_: Int))
and so your addition overflows and gives you something smaller than 2000000000 (9 zeroes, Int.MaxValue = 2147483647).

compiler error message when using State monad for memoization

I have a problem to make a working version of the Euler project problem 31 with the use of State trait (inspired from scalaz)
First, I have a solution with a mutable HashMap for memoization. It works but i would like to use the State monad, to understand it and to improve my skills.
I have used it with the fibonacci example, but when i attempt to apply the same technique to my case, i have a compiler error that i don't understand.
I use this implementation for State :
trait State[S, A] {
val run: S => (S, A)
def apply(s: S): (S, A) = run(s)
def eval(s: S): A = run(s)._2
def map[B](f: A => B): State[S, B] =
State { s: S =>
val (s1, a) = run(s)
(s1, f(a))
}
def flatMap[B](f: A => State[S, B]): State[S, B] =
State { s: S =>
val (s1, a) = run(s)
f(a)(s1)
}
}
object State {
def apply[S, A](f: S => (S, A)): State[S, A] = new State[S, A] {
final val run = f
}
def init[S, A](a: A) = State { s: S => (s, a) }
def update[S, A](f: S => S): State[S, Unit] = State { s: S => (f(s), ()) }
def gets[S, A](f: S => A): State[S, A] = State { s: S => (s, f(s)) }
}
my attempt to use it is here :
val coins = List(1, 2, 5, 10, 20, 50, 100, 200)
type MemoKey = (List[Int], Int)
type MemoType = Map[MemoKey, Int]
def ways(listCoins: List[Int], amount: Int): Int = {
def ways_impl(coins: List[Int], sum: Int): State[MemoType, Int] = (coins, sum) match {
case (Nil, 0) => State.init(1)
case (Nil, _) => State.init(0)
case (c :: cs, _) =>
for {
memoed <- State.gets { m: MemoType => m.get((coins, sum)) }
res <- memoed match {
case Some(way) => State.init[MemoType, Int](way)
case None =>
(for {
i <- 0 to sum / c
r <- ways_impl(cs, sum - i * c)
_ <- State.update { m: MemoType => m + ((coins, sum) -> r) }
} yield r).sum
}
} yield res
}
ways_impl(listCoins, amount) eval (Map())
I have a compiler error at this line :
r <- ways_impl(cs, sum - i * c)
The compiler said :
type mismatch; found : State[MemoType,Int] (which expands to) State[scala.collection.immutable.Map[(List[Int], Int),Int],Int] required: scala.collection.GenTraversableOnce[?]
For information, here is my first version with mutable map :
import scala.collection.mutable._
val memo = HashMap[(List[Int], Int), Int]()
val coins = List(1, 2, 5, 10, 20, 50, 100, 200)
def memoWays(coins: List[Int], sum: Int): Int = {
memo.getOrElse((coins, sum), {
val y = ways(coins, sum)
memo += ((coins, sum) -> y)
y
})
}
// brute force method with memoization
def ways(coins: List[Int], sum: Int): Int = (coins, sum) match {
case (Nil, 0) => 1
case (Nil, _) => 0
case (c :: cs, n) =>
(for {
i <- 0 to n / c
r = memoWays(cs, n - i * c)
} yield r).sum
}
println(s"result=${Mesure(ways(coins, 200))}")
What does that error mean ? Why the compiler want a GenTraversableOnce instead of State ?
What kind of thing i don't understand on State monad ?
And, if i may, I have an optional question :
Is my way to memoize with State Monad, is a good choice, or my first implementation with mutable map is better anyway ?
The problem is that your for comprehension is attempting to flatMap two unrelated types: a Range and a State. You're going to have to refactor, although off the top of my head, it's not clear to me how you'll be able to leverage State in a simple way. I'd probably use an immutable Map for the memo, a List to represent the future iterations to be tried, and simple recursion to iterate.

Implement fold with for-comprehension

How can a fold be implemented as a for-comprehension in Scala? I see the only way is to use some recursive call? This is a try that is failing, not sure how to do this? What is the best way to implement fold as a for-comprehension
val nums = List(1,2,3)
nums.fold(0)(_+_)
def recFold(acc: Int = 0): Int = {
(for {
a <- nums
b = recFold(a + acc)
} yield b).head
}
recFold(0) //Stack overflow
If you really want to use for, you don't need recursion, but you would need a mutable variable:
val nums = List(1,2,3)
def recFold(zero: Int)(op: (Int, Int) => Int): Int = {
var result: Int = zero
for { a <- nums } result = op(result, a)
result
}
recFold(0)(_ + _) // 6
Which is pretty similar to how foldLeft is actually implemented in TraversableOnce:
def foldLeft[B](z: B)(op: (B, A) => B): B = {
var result = z
this foreach (x => result = op(result, x))
result
}
Fold can be implemented both ways right to left or left to right. No need to use for plus recursion. Recursion is enough.
def foldRight[A, B](as: List[A], z: B)(f: (A, B) => B): B = {
as match {
case Nil => z
case x :: xs => f(x, foldRight(xs, z)(f))
}
}
#annotation.tailrec
def foldLeft[A, B](as: List[A], z: B)(f: (A, B) => B): B = {
as match {
case Nil => z
case x :: xs => foldLeft(xs, f(x, z))(f)
}
}

Partition a sequence of disjunctions in Scalaz

What is the best way to partition Seq[A \/ B] into (Seq[A], Seq[B]) using Scalaz?
There is a method: separate defined in MonadPlus. This typeclass is a combination a Monad with PlusEmpty (generalized Monoid). So you need to define instance for Seq:
1) MonadPlus[Seq]
implicit val seqmp = new MonadPlus[Seq] {
def plus[A](a: Seq[A], b: => Seq[A]): Seq[A] = a ++ b
def empty[A]: Seq[A] = Seq.empty[A]
def point[A](a: => A): Seq[A] = Seq(a)
def bind[A, B](fa: Seq[A])(f: (A) => Seq[B]): Seq[B] = fa.flatMap(f)
}
Seq is already monadic, so point and bind are easy, empty and plus are monoid operations and Seq is a free monoid
2) Bifoldable[\/]
implicit val bife = new Bifoldable[\/] {
def bifoldMap[A, B, M](fa: \/[A, B])(f: (A) => M)(g: (B) => M)(implicit F: Monoid[M]): M = fa match {
case \/-(r) => g(r)
case -\/(l) => f(l)
}
def bifoldRight[A, B, C](fa: \/[A, B], z: => C)(f: (A, => C) => C)(g: (B, => C) => C): C = fa match {
case \/-(r) => g(r, z)
case -\/(l) => f(l, z)
}
}
Also easy, standard folding, but for type constructors with two parameters.
Now you can use separate:
val seq: Seq[String \/ Int] = List(\/-(10), -\/("wrong"), \/-(22), \/-(1), -\/("exception"))
scala> seq.separate
res2: (Seq[String], Seq[Int]) = (List(wrong, number exception),List(10, 22, 1))
Update
Thanks to Kenji Yoshida, there is a Bitraverse[\/], so you need only MonadPlus.
And a simple solution using foldLeft:
seq.foldLeft((Seq.empty[String], Seq.empty[Int])){ case ((as, ai), either) =>
either match {
case \/-(r) => (as, ai :+ r)
case -\/(l) => (as :+ l, ai)
}
}