I've used cats for the first time to solve day 1 of advent of code and I'm wondering if it's possible to improve things.
Given a method update with the following signature
def update(i: Instruction): PosAndDir => PosAndDir
I've come up with :
val state: State[PosAndDir, List[Unit]] = instructions.map(i => State.modify(update(i))).toList.sequenceU
val finalState = state.runS(PosAndDir(Pos(0, 0), North)).value
And also
def update2(i: Instruction): State[PosAndDir, Option[Pos]] =
State.modify(update(i)).inspect(pad => if (i == Walk) Some(pad.pos) else None)
…
val state = instructions.map(update2).toList.sequenceU
val positions = state.runA(PosAndDir(Pos(0, 0), North)).value.flatten
More precisely, questions are :
why do we need to call .value (with scalaz, it's transparent) ?
is there a way to write update2 with a for comprehension to improve readability ?
is there an Applicative instance for Seq in cats (I know there is not in scalaz). ?
any idea to improve the code ?
cats defines State[S, A] as an alias for stack-safe StateT[Eval, S , A] which is StateT[Trampoline, S, A] in scalaz terms, so runS returns Eval[A], where value will be run without stackoverflow even for very long flatMap sequences.
Using some more additional imports
import cats.data.{State, StateT}
import cats.MonadState
import cats.syntax.functorFilter._
import cats.instances.option._
and some preparations
type Walk[x] = StateT[Option, PosAndDir, x]
val stateMonad = MonadState[Walk, PosAndDir]
import stateMonad._
you can make your function look like this
def update2(i: Instruction): StateT[Option, PosAndDir, Pos] =
for (pad ← get if i == Walk) yield pad.pos
not that this solution will not work in 2.12 due to this improvement, you can make it work with this workaround
implicit class FunctorWithFilter[F[_] : FunctorFilter, A](fa: F[A]) {
def withFilter(f: A ⇒ Boolean) = fa.filter(f)
}
There is no instances for Seq, this answer describes why. While there are some non-orthodox instances in the alleycats project. I'm not really sure if you need for Applicative[Seq], from your code you are rather have need for Traverse[Seq], or if you replace your sequence with sequence_ even Foldable[Seq].
Good news there is Foldable[Iterable] in the alleycats, and here is my attempt to define something lookalike for Seq instance
implicit val seqInstance = new MonadFilter[Seq] with Traverse[Seq] {
def traverse[G[_] : Applicative, A, B](fa: Seq[A])(f: (A) ⇒ G[B]): G[Seq[B]] =
fa match {
case head +: tail ⇒ f(head).map2(traverse(tail)(f))(_ +: _)
case _empty ⇒ Seq.empty[B].pure[G]
}
def foldLeft[A, B](fa: Seq[A], b: B)(f: (B, A) ⇒ B): B = fa.foldLeft(b)(f)
def foldRight[A, B](fa: Seq[A], lb: Eval[B])(f: (A, Eval[B]) ⇒ Eval[B]): Eval[B] =
fa match {
case head +: tail ⇒ f(head, foldRight(tail, lb)(f))
case _empty ⇒ lb
}
def pure[A](x: A): Seq[A] = Seq(x)
def empty[A]: Seq[A] = Seq.empty[A]
def flatMap[A, B](fa: Seq[A])(f: (A) ⇒ Seq[B]): Seq[B] = fa.flatMap(f)
def tailRecM[A, B](a: A)(f: (A) ⇒ Seq[Either[A, B]]): Seq[B] = {
#tailrec def go(seq: Seq[Either[A, B]]): Seq[B] =
if (seq.contains((_: Either[A, B]).isLeft))
go(seq.flatMap {
case Left(a) ⇒ f(a)
case b ⇒ Seq(b)
}) else seq.collect { case Right(b) ⇒ b }
go(Seq(Left(a)))
}
override def mapFilter[A, B](fa: Seq[A])(f: (A) ⇒ Option[B]): Seq[B] =
fa.flatMap(f(_).toSeq)
}
didn't spent much time but here is my attempt to simplifying some parts via the Monocle library:
import cats.{MonadState, Foldable, Functor}
import cats.instances.option._
import cats.syntax.foldable._
import cats.syntax.functor._
import cats.syntax.functorFilter._
import monocle.macros.Lenses
#Lenses
case class Pos(x: Int, y: Int)
sealed abstract class Dir(val cmd: Pos ⇒ Pos)
case object South extends Dir(Pos.y.modify(_ - 1))
case object North extends Dir(Pos.y.modify(_ + 1))
case object East extends Dir(Pos.x.modify(_ + 1))
case object West extends Dir(Pos.x.modify(_ - 1))
#Lenses
case class PosAndDir(pos: Pos, dir: Dir)
val clockwise = Vector(North, East, South, West)
val right: Map[Dir, Dir] = clockwise.zip(clockwise.tail :+ clockwise.head).toMap
val left: Map[Dir, Dir] = right.map(_.swap)
sealed abstract class Instruction(val cmd: PosAndDir ⇒ PosAndDir)
case object TurnLeft extends Instruction(PosAndDir.dir.modify(left))
case object TurnRight extends Instruction(PosAndDir.dir.modify(right))
case object Walk extends Instruction(pd ⇒ PosAndDir.pos.modify(pd.dir.cmd)(pd))
def runInstructions[F[_] : Foldable : Functor](instructions: F[Instruction])(start: PosAndDir): PosAndDir =
instructions.map(i => State.modify(i.cmd)).sequence_.runS(start).value
Related
I'm reading the scala-with-cats book and follow it's exercise. When I come to the case study: data validation, I encounter some problems.
Here is my entire code (just the same with the book):
package org.scala.ch10.final_recap
import cats.Semigroup
import cats.data.Validated
import cats.data.Validated._
import cats.data.Kleisli
import cats.data.NonEmptyList
import cats.instances.either._
import cats.syntax.apply._
import cats.syntax.semigroup._
import cats.syntax.validated._
sealed trait Predicate[E, A] {
import Predicate._
def and(that: Predicate[E, A]): Predicate[E, A] =
And(this, that)
def or(that: Predicate[E, A]): Predicate[E, A] =
Or(this, that)
/**
* This part is for Kleislis
* #return
*/
def run(implicit s: Semigroup[E]): A => Either[E, A] =
(a: A) => this(a).toEither
def apply(a: A)(implicit s: Semigroup[E]): Validated[E, A] =
this match {
case Pure(func) =>
func(a)
case And(left, right) => (left(a), right(a)).mapN((_, _) => a)
case Or(left, right) =>
left(a) match {
case Valid(_) => Valid(a)
case Invalid(e1) =>
right(a) match {
case Valid(_) => Invalid(e1)
case Invalid(e2) => Invalid(e1 |+| e2)
}
}
}
}
object Predicate {
final case class And[E, A](left: Predicate[E, A], right: Predicate[E, A]) extends Predicate[E, A]
final case class Or[E, A](left: Predicate[E, A], right: Predicate[E, A]) extends Predicate[E, A]
final case class Pure[E, A](func: A => Validated[E, A]) extends Predicate[E, A]
def apply[E, A](f: A => Validated[E, A]): Predicate[E, A] = Pure(f)
def lift[E, A](err: E, fn: A => Boolean): Predicate[E, A] = Pure(a => if(fn(a)) a.valid else err.invalid)
}
object FinalRecapPredicate {
type Errors = NonEmptyList[String]
def error(s: String): NonEmptyList[String] = NonEmptyList(s, Nil)
type Result[A] = Either[Errors, A]
type Check[A, B] = Kleisli[Result, A, B]
def check[A, B](func: A => Result[B]): Check[A, B] = Kleisli(func)
def checkPred[A](pred: Predicate[Errors, A]): Check[A, A] =
Kleisli[Result, A, A](pred.run)
def longerThan(n: Int): Predicate[Errors, String] =
Predicate.lift(
error(s"Must be longer than $n characters"),
str => str.length > n
)
val alphanumeric: Predicate[Errors, String] =
Predicate.lift(
error(s"Must be all alphanumeric characters"),
str => str.forall(_.isLetterOrDigit)
)
def contains(char: Char): Predicate[Errors, String] =
Predicate.lift(
error(s"Must contain the character $char"),
str => str.contains(char)
)
def containsOnce(char: Char): Predicate[Errors, String] =
Predicate.lift(
error(s"Must contain the character $char only once"),
str => str.count(_ == char) == 1
)
val checkUsername: Check[String, String] = checkPred(longerThan(3) and alphanumeric)
val splitEmail: Check[String, (String, String)] = check(_.split('#') match {
case Array(name, domain) =>
Right((name, domain))
case _ =>
Left(error("Must contain a single # character"))
})
val checkLeft: Check[String, String] = checkPred(longerThan(0))
val checkRight: Check[String, String] = checkPred(longerThan(3) and contains('.'))
val joinEmail: Check[(String, String), String] =
check {
case (l, r) => (checkLeft(l), checkRight(r)).mapN(_ + "#" + _)
}
val checkEmail: Check[String, String] = splitEmail andThen joinEmail
final case class User(username: String, email: String)
def createUser(username: String, email: String): Either[Errors, User] =
(checkUsername.run(username),
checkEmail.run(email)).mapN(User)
def main(args: Array[String]): Unit = {
println(createUser("", "noel#underscore.io#io"))
}
}
It supposes the code should end up with the error message Left(NonEmptyList(Must be longer than 3 characters), Must contain a single # character) But what I actually is Left(NonEmptyList(Must be longer than 3 characters))
Obviously, it does not work as expected. It fails fast instead of accumulating errors... How to fix that plz? (I've spent hours now and can't get a workaround)
This is the "problematic" part:
def createUser(username: String, email: String): Either[Errors, User] =
(checkUsername.run(username),
checkEmail.run(email)).mapN(User)
You are combining a tuple of Results, where
type Result[A] = Either[Errors, A]
This means you are really doing a mapN on a pair of Eithers, an operation provided by the Semigroupal type class. This operation will not accumulate results.
There are several reasons for this, but one that I find particularly important is the preserving of behaviour if we find ourselves using a Semigroupal / Applicative which also happens to be a Monad. Why is that a problem? Because Monads are sequencing operations, making each step depend on the previous one, and having "fail early" semantics. When using some Monad, one might expect those semantics to be preserved when using constructs from the underlying Applicative (every Monad is also an Applicative). In that case, if the implementation of Applicative used "accumulation" semantics instead of "fail early" semantics, we would ruin some important laws like referential transparency.
You can use a parallel version of mapN, called parMapN, whose contract guarantees that the implementation will be evaluating all results in parallel. This means that it definitely cannot be expected to have the "fail early" semantics, and accumulating results is fine in that case.
Note that Validated accumulates results as well, usually in a NonEmptyList or a NonEmptyChain. This is probably why you expected to see your accumulated results; the only problem is, you were not using Validated values in the "problematic" part of your code, but raw Eithers instead.
Here's some simple code that demonstrates the above concepts:
import cats.data._
import cats.implicits._
val l1: Either[String, Int] = Left("foo")
val l2: Either[String, Int] = Left("bar")
(l1, l2).mapN(_ + _)
// Left(foo)
(l1, l2).parMapN(_ + _)
// Left(foobar)
val v1: ValidatedNel[String, Int] = l1.toValidatedNel
val v2: ValidatedNel[String, Int] = l2.toValidatedNel
(v1, v2).mapN(_ + _)
// Invalid(NonEmptyList(foo, bar))
Note - the operation described below now exists in the standard library as partitionMap but I believe it's still a valid question as to how to achieve more general ends
Question regarding scala 2.13 - how do I consume/construct collections of specific types when adding custom collections operations where I need to restrict the element types of the input collections? e.g. how do I define:
def split[CC[_], A, B](coll: CC[Either[A, B]]): (CC[A], CC[B])
Following the documentation I've managed to achieve this as follows:
import collection.generic.IsIterable
import scala.collection.{BuildFrom, Factory}
class SplitOperation[Repr, S <: IsIterable[Repr]](coll: Repr, itr: S) {
def split[A, B, AS, BS](
implicit bfa: BuildFrom[Repr, A, AS],
bfb: BuildFrom[Repr, B, BS],
ev: itr.A =:= Either[A, B]): (AS, BS) = {
val ops = itr(coll)
val as = bfa.fromSpecific(coll)(ops.iterator.map(ev).collect { case Left(a) => a })
val bs = bfb.fromSpecific(coll)(ops.iterator.map(ev).collect { case Right(b) => b })
(as, bs)
}
}
implicit def SplitOperation[Repr](coll: Repr)(implicit itr: IsIterable[Repr]): SplitOperation[Repr, itr.type] =
new SplitOperation(coll, itr)
However, I need to supply types at the use-site otherwise I get diverging implicit expansion.
scala> List(Left("bah"), Right(1), Left("gah"), Right(2), Right(3))
res1: List[scala.util.Either[String,Int]] = List(Left(bah), Right(1), Left(gah), Right(2), Right(3))
scala> res1.split
^
error: diverging implicit expansion for type scala.collection.BuildFrom[List[scala.util.Either[String,Int]],A,AS]
But the following works:
scala> res1.split[String, Int, List[String], List[Int]]
res4: (List[String], List[Int]) = (List(bah, gah),List(1, 2, 3))
EDIT
class SplitOperation[X, CC[_], S <: IsIterable[CC[X]]](coll: CC[X], itr: S) {
def split[A, B](implicit bfa: BuildFrom[CC[X], A, CC[A]], bfb: BuildFrom[CC[X], B, CC[B]], ev: itr.A =:= Either[A, B]): (CC[A], CC[B]) = {
val ops = itr(coll)
val as = bfa.fromSpecific(coll)(ops.iterator.map(ev).collect { case Left(a) => a })
val bs = bfb.fromSpecific(coll)(ops.iterator.map(ev).collect { case Right(b) => b })
(as, bs)
}
}
implicit def SplitOperation[A, B, CC[_]](coll: CC[Either[A, B]])(implicit itr: IsIterable[CC[Either[A, B]]]): SplitOperation[Either[A, B], CC, itr.type] =
new SplitOperation(coll, itr)
Gives me a slight improvement. Now I only need to provide type parameters A and B at the call site:
scala> l.split[String, Int]
res2: (List[String], List[Int]) = (List(bah, gah),List(1, 2))
This seems to work:
class SplitOperation[A, B, CC[_], S <: IsIterable[CC[Either[A, B]]]](coll: CC[Either[A, B]], itr: S) {
def split(implicit bfa: BuildFrom[CC[Either[A, B]], A, CC[A]], bfb: BuildFrom[CC[Either[A, B]], B, CC[B]], ev: itr.A =:= Either[A, B]): (CC[A], CC[B]) = {
val ops = itr(coll)
val as = bfa.fromSpecific(coll)(ops.iterator.map(ev).collect { case Left(a) => a })
val bs = bfb.fromSpecific(coll)(ops.iterator.map(ev).collect { case Right(b) => b })
(as, bs)
}
}
implicit def SplitOperation[A, B, CC[_]](coll: CC[Either[A, B]])(implicit itr: IsIterable[CC[Either[A, B]]]): SplitOperation[A, B, CC, itr.type] =
new SplitOperation(coll, itr)
In your case you don’t want to abstract over the “kind” of the collection type constructor (CC[_] vs CC[_, _], etc.), you always use the CC[_] kind, so you don’t need to use IsIterable.
I think it is also not necessary to support “Sorted” collections (eg, SortedSet) because there is no Ordering instance for Either, so you don’t need to use BuildFrom.
implicit class SplitOperation[A, B, CC[X] <: IterableOps[X, CC, CC[X]]](coll: CC[Either[A, B]]) {
def split: (CC[A], CC[B]) = {
val as = coll.iterableFactory.from(coll.iterator.collect { case Left(a) => a })
val bs = coll.iterableFactory.from(coll.iterator.collect { case Right(b) => b })
(as, bs)
}
}
https://scastie.scala-lang.org/64QxHwteQN2i3udSxCa3yw
I know I can traverse Lists
import cats.instances.list._
import cats.syntax.traverse._
def doMagic(item: A): M[B] = ???
val list: List[A] = ???
val result: M[List[B]] = list.traverse(doMagic)
And I can convert a Seq back and forth to List
val seq: Seq[A] = ???
val result: M[Seq[B]] = seq.toList.traverse(doMagic).map(_.toSeq)
But can I also traverse Seq without the boilerplate?
val seq: Seq[A] = ???
val result: M[Seq[B]] = seq.traverse(doMagic)
Or what's an easy way to get an instance of Traverse[Seq]?
Cats does not provide typeclass instances for Seq, so besides implementing it yourself you're stuck with the conversion.
As to why, there's an ongoing discussion in an (somewhat old) Cats issue. To sum it up, you won't know enough about Seq underlying characteristics to make sure some of the typeclasses instances laws hold.
EDIT : Nevermind, it exists now, see linked thread
As of cats 2.3, support for immutable.Seq is now built in. See "Where are implicit instances for Seq?" on the FAQ or this PR where the functionality was added.
If you are absolutely sure that the conversion from all Seq to List will always succeed in your code, you can simply transfer the Traverse structure from List to Seq over an (pseudo-)isomorphism:
def traverseFromIso[F[_], Z[_]]
(forward: F ~> Z, inverse: Z ~> F)
(implicit zt: Traverse[Z])
: Traverse[F] = new Traverse[F] {
def foldLeft[A, B](fa: F[A], b: B)(f: (B, A) ⇒ B): B = zt.foldLeft(forward(fa), b)(f)
def foldRight[A, B](fa: F[A], lb: Eval[B])(f: (A, Eval[B]) => Eval[B]): Eval[B] =
zt.foldRight(forward(fa), lb)(f)
def traverse[G[_], A, B]
(fa: F[A])
(f: (A) ⇒ G[B])
(implicit appG: Applicative[G])
: G[F[B]] = {
(zt.traverse(forward(fa))(f)(appG)).map(zb => inverse(zb))
}
}
This isn't really an isomorphism, because the conversion from Seq to List can fail badly (e.g. if the sequence is infinite). What it does is simply converting Seq to List back and forth, and forwarding all method calls to those of Traverse[List].
Now you can use this method to build an instance of Traverse[Seq]:
implicit val seqTraverse: Traverse[Seq] = traverseFromIso(
new FunctionK[Seq, List] { def apply[X](sx: Seq[X]): List[X] = sx.toList },
new FunctionK[List, Seq] { def apply[X](lx: List[X]): Seq[X] = lx }
)
Full code snippet (compiles with scala 2.12.4 and cats 1.0.1):
import cats._
import cats.implicits._
import cats.arrow.FunctionK
import scala.language.higherKinds
object TraverseFromIso {
// This method can build you a `Traversable[Seq]` from
// an `Traversable[List]` and a pair of polymorphic conversion
// functions:
def traverseFromIso[F[_], Z[_]]
(forward: F ~> Z, inverse: Z ~> F)
(implicit zt: Traverse[Z])
: Traverse[F] = new Traverse[F] {
def foldLeft[A, B](fa: F[A], b: B)(f: (B, A) ⇒ B): B = zt.foldLeft(forward(fa), b)(f)
def foldRight[A, B](fa: F[A], lb: Eval[B])(f: (A, Eval[B]) => Eval[B]): Eval[B] =
zt.foldRight(forward(fa), lb)(f)
def traverse[G[_], A, B]
(fa: F[A])
(f: (A) ⇒ G[B])
(implicit appG: Applicative[G])
: G[F[B]] = {
(zt.traverse(forward(fa))(f)(appG)).map(zb => inverse(zb))
}
}
// A little demo
def main(args: Array[String]): Unit = {
// To instantiate a `Traverse[Seq]`, we have to provide
// two natural transformations (from List to Seq and back):
implicit val seqTraverse: Traverse[Seq] = traverseFromIso(
new FunctionK[Seq, List] { def apply[X](sx: Seq[X]): List[X] = sx.toList },
new FunctionK[List, Seq] { def apply[X](lx: List[X]): Seq[X] = lx }
)
// do stuff with `Traversable[Seq]` here
}
}
I am looking at this question from Scala and Scalaz angles. OptionT works for Future but not Try. What is the reason there is no OptionT for Try where there is a usecase a function i.e. def foo(i: Int): Try[Option[Int]] = ... may or not return a value and occasionally network exception will happen? Thanks
The reason is Try isn't a valid functor.
You'll need to use scalaz-outlaws or write your own Try instances. Here's a working example using scalaz-outlaws' Try instances:
import scala.util.{Try,Success,Failure}
import scalaz._
import Scalaz._
implicit val tryOutlawInstances = new Traverse[Try] with Monad[Try] with Plus[Try]{
def point[A](a: ⇒ A): Try[A] = Success(a)
override def map[A,B](fa: Try[A])(f: A ⇒ B) = fa map f
def bind[A,B](fa: Try[A])(f: A ⇒ Try[B]) = fa flatMap f
def traverseImpl[F[_], A, B](fa: Try[A])(f: A ⇒ F[B])(implicit F: Applicative[F]) : F[Try[B]] = fa match {
case Success(a) ⇒ F.map(f(a))(Success.apply)
case Failure(f) ⇒ F.point(Failure(f))
}
def plus[A](a: Try[A], b: ⇒ Try[A]) = a orElse b
}
val foo = Try("foo".some)
val result = OptionT(foo).map(x => x.toUpperCase).run
This is a followup to my previous question with an example found on the Internet.
Suppose I define a typeclass Applicative as follows:
trait Functor[T[_]]{
def map[A,B](f:A=>B, ta:T[A]):T[B]
}
trait Applicative[T[_]] extends Functor[T] {
def unit[A](a:A):T[A]
def ap[A,B](tf:T[A=>B], ta:T[A]):T[B]
}
I can define an instance of Applicative for List
object AppList extends Applicative[List] {
def map[A,B](f:A=>B, as:List[A]) = as.map(f)
def unit[A](a: A) = List(a)
def ap[A,B](fs:List[A=>B], as:List[A]) = for(f <- fs; a <- as) yield f(a)
}
For convenience I can define an implicit conversion to add a method <*> to List[A=>B]
implicit def toApplicative[A, B](fs: List[A=>B]) = new {
def <*>(as: List[A]) = AppList.ap(fs, as)
}
Now I can do a cool thing !
zip two lists List[String] and apply f2 to every pair in applicative style
val f2: (String, String) => String = {(first, last) => s"$first $last"}
val firsts = List("a", "b", "c")
val lasts = List("x", "y", "z")
scala> AppList.unit(f2.curried) <*> firsts <*> lasts
res31: List[String] = List(a x, a y, a z, b x, b y, b z, c x, c y, c z)
So far, so good but now I have:
val firstsOpt = Some(firsts)
val lastsOpt = Some(lasts)
I would like to zip firsts and lasts, apply f2, and get Option[List[String]] in applicative style. In other words I need <*> for Option[List[_]]. How can I do it ?
Firstly, you need an instance of applicative for Option:
implicit object AppOption extends Applicative[Option] {
def map[A, B](f: A => B, o: Option[A]) = o.map(f)
def unit[A](a: A): Option[A] = Some(a)
def ap[A, B](of: Option[A => B], oa: Option[A]) = of match {
case Some(f) => oa.map(f)
case None => None
}
}
Then you can also create an applicative instance for the composition of two applicatives (note, based on the Haskell version):
class AppComp[F[_], G[_]](fa: Applicative[F], ga: Applicative[G]) extends Applicative[({ type f[A] = F[G[A]]})#f] {
def map[A, B](f: A => B, a: F[G[A]]): F[G[B]] = fa.map((g: G[A]) => ga.map(f, g), a)
def unit[A](a: A) = fa.unit(ga.unit(a))
def ap[A, B](f: F[G[A => B]], a: F[G[A]]): F[G[B]] = {
val liftg: G[A => B] => (G[A] => G[B]) = gf => (gx => ga.ap(gf, gx))
val ffg: F[G[A] => G[B]] = fa.map(liftg, f)
fa.ap(ffg, a)
}
}
implicit def toComp[F[_], G[_]](implicit fa: Applicative[F], ga: Applicative[G]) = new AppComp[F, G](fa, ga)
Finally you can now do:
val ola = toComp[Option, List]
ola.ap(ola.ap(ola.unit(f2.curried), firstsOpt), lastsOpt)
You could probably also remove some of the noise by generalising <*> to work for any applicative.