Convert expression to polish notation in Scala - scala

I would like to convert an expression such as: a.meth(b) to a function of type (A, B) => C that performs that exact computation.
My best attempt so far was along these lines:
def polish[A, B, C](symb: String): (A, B) => C = { (a, b) =>
// reflectively check if "symb" is a method defined on a
// if so, reflectively call symb, passing b
}
And then use it like this:
def flip[A, B, C](f : (A, B) => C): (B, A) => C = {(b, a) => f(a,b)}
val op = flip(polish("::"))
def reverse[A](l: List[A]): List[A] = l reduceLeft op
As you can pretty much see, it is quite ugly and you have to do a lot of type checking "manually".
Is there an alternative ?

You can achieve it easily with plain old subtype polymorphism. Just declare interface
trait Iface[B, C] {
def meth(b: B): C
}
Then you could implement polish easily
def polish[B, C](f: (Iface[B, C], B) => C): (Iface[B, C], B) => C = { (a, b) =>
f(a, b)
}
Using it is completely typesafe
object IfaceImpl extends Iface[String, String] {
override def meth(b: String): String = b.reverse
}
polish((a: Iface[String, String], b: String) => a meth b)(IfaceImpl, "hello")
Update:
Actually, you could achieve it using closures only
def polish[A, B, C](f: (A, B) => C): (A, B) => C = f
class Foo {
def meth(b: String): String = b.reverse
}
polish((_: Foo) meth (_: String))(new Foo, "hello")
Or without helper function at all :)
val polish = identity _ // Magic at work
((_: Foo) meth (_: String))(new Foo, "hello")

Related

scala generic function reference

I have several generic functions with the same signature:
def f1[A, B](v: A, f: (A, B) => B): B = ...
def f2[A, B](v: A, f: (A, B) => B): B = ...
And I need to define a function g that can accept any of these functions (f1 f2):
def g(f: ????) = ...
g internally uses multiple argument types, so I can not parameterize it like that:
def g[A, B](f: (A, (A, B) => B) => B) = ...
There isn't really a much better way to do it in Scala 2. Although your solution is a bit strange because FunctionHolder's apply method will return a function object and doesn't accept any arguments itself – that's a bit more complicated than it needs to be. So you can do this instead:
trait FunctionHolder {
def apply[A, B](v: A, f: (A, B) => B): B
}
def g(f: FunctionHolder) = …
But this isn't really all that much better.
In Scala 3, there are polymorphic function types to do this in a cleaner way:
def g(f: [A, B] => (A, (A, B) => B) => B) = …
That said, I'm not convinced that that type signature is really what you want. Remember, when you define a function with type parameters, it needs to work for all possible type parameters that the user might supply. This can't be done for this signature…
def f1[A, B](v: A, f: (A, B) => B): B
… because when I have a function like that, I can easily write an expression of type Nothing:
f1[Unit, Nothing]((), (a: Unit, b: Nothing) => b)
and it's not possible to write an expression of type Nothing unless you cheat (e. g. throw an exception or enter an infinite loop or something like that). So the type signature tells me you're cheating 😉
If you want to know more about this kind of reasoning, search for “Theorems for free!”
After wandering a bit, come up with following:
g(new FunctionHolder {
def apply[A, B](): (A, (A, B) => B) => B = f1
})
def g(f: FunctionHolder) = f()(..., (a, b) => ...)
abstract class FunctionHolder {
def apply[A, B](): (A, (A, B) => B) => B
}
But that just does not look right.
Hope there are more concise ways to do that

Programming a state monad in Scala

The theory of how a state monad looks like I borrow from Philip Wadler's Monads for Functional Programming:
type M a = State → (a, State)
type State = Int
unit :: a → M a
unit a = λx. (a, x)
(*) :: M a → (a → M b) → M b
m * k = λx.
let (a, y) = m x in
let (b, z) = k a y in
(b, z)
The way I would like to use a state monad is as follows:
Given a list L I want different parts of my code to get this list and update this list by adding new elements at its end.
I guess the above would be modified as:
type M = State → (List[Data], State)
type State = List[Data]
def unit(a: List[Data]) = (x: State) => (a,x)
def star(m: M, k: List[Data] => M): M = {
(x: M) =>
val (a,y) = m(x)
val (b,z) = k(a)(y)
(b,z)
}
def get = ???
def update = ???
How do I fill in the details, i.e.?
How do I instantiate my hierarchy to work on a concrete list?
How do I implement get and update in terms of the above?
Finally, how would I do this using Scala's syntax with flatMap and unit?
Your M is defined incorrectly. It should take a/A as a parameter, like so:
type M[A] = State => (A, State)
You've also missed that type parameter elsewhere.
unit should have a signature like this:
def unit[A](a: A): M[A]
star should have a signature like this:
def star[A, B](m: M[A], k: A => M[B]): M[B]
Hopefully, that makes the functions more clear.
Your implementation of unit was pretty much the same:
def unit[A](a: A): M[A] = x => (a, x)
However, in star, the parameter of your lambda (x) is of type State, not M, because M[B] is basically State => (A, State). The rest you got right:
def star[A, B](m: M[A])(k: A => M[B]): M[B] =
(x: State) => {
val (a, y) = m(x)
val (b, z) = k(a)(y)
(b, z)
}
Edit: According to #Luis Miguel Mejia Suarez:
It would probably be easier to implement if you make your State a class and define flatMap inside it. And you can define unit in the companion object.
He suggested final class State[S, A](val run: S => (A, S)), which would also allow you to use infix functions like >>=.
Another way to do it would be to define State as a type alias for a function S => (A, S) and extend it using an implicit class.
type State[S, A] = S => (A, S)
object State {
//This is basically "return"
def unit[S, A](a: A): State[S, A] = s => (a, s)
}
implicit class StateOps[S, A](private runState: S => (A, S)) {
//You can rename this to ">>=" or "flatMap"
def *[B](k: A => State[S, B]): State[S, B] = s => {
val (a, s2) = runState(s)
k(a)(s2)
}
}
If your definition of get is
set the result value to the state and leave the state unchanged
(borrowed from Haskell Wiki), then you can implement it like this:
def get[S]: State[S, S] = s => (s, s)
If you mean that you want to extract the state (in this case a List[Data]), you can use execState (define it in StateOps):
def execState(s: S): S = runState(s)._2
Here's a terrible example of how you can add elements to a List.
def addToList(n: Int)(list: List[Int]): ((), List[Int]) = ((), n :: list)
def fillList(n: Int): State[List[Int], ()] =
n match {
case 0 => s => ((), s)
case n => fillList(n - 1) * (_ => addToList(n))
}
println(fillList(10)(List.empty)) gives us this (the second element can be extracted with execState):
((),List(10, 9, 8, 7, 6, 5, 4, 3, 2, 1))

How to compose two different `State Monad`?

When I learn State Monad, I'm not sure how to compose two functions with different State return types.
State Monad definition:
case class State[S, A](runState: S => (S, A)) {
def flatMap[B](f: A => State[S, B]): State[S, B] = {
State(s => {
val (s1, a) = runState(s)
val (s2, b) = f(a).runState(s1)
(s2, b)
})
}
def map[B](f: A => B): State[S, B] = {
flatMap(a => {
State(s => (s, f(a)))
})
}
}
Two different State types:
type AppendBang[A] = State[Int, A]
type AddOne[A] = State[String, A]
Two methods with differnt State return types:
def addOne(n: Int): AddOne[Int] = State(s => (s + ".", n + 1))
def appendBang(str: String): AppendBang[String] = State(s => (s + 1, str + " !!!"))
Define a function to use the two functions above:
def myAction(n: Int) = for {
a <- addOne(n)
b <- appendBang(a.toString)
} yield (a, b)
And I hope to use it like this:
println(myAction(1))
The problem is myAction is not compilable, it reports some error like this:
Error:(14, 7) type mismatch;
found : state_monad.State[Int,(Int, String)]
required: state_monad.State[String,?]
b <- appendBang(a.toString)
^
How can I fix it? Do I have to define some Monad transformers?
Update: The question may be not clear, let me give an example
Say I want to define another function, which uses addOne and appendBang internally. Since they all need existing states, I have to pass some to it:
def myAction(n: Int)(addOneState: String, appendBangState: Int): ((String, Int), String) = {
val (addOneState2, n2) = addOne(n).runState(addOneState)
val (appendBangState2, n3) = appendBang(n2.toString).runState(appendBangState)
((addOneState2, appendBangState2), n3)
}
I have to run addOne and appendBang one by one, passing and getting the states and result manually.
Although I found it can return another State, the code is not improved much:
def myAction(n: Int): State[(String, Int), String] = State {
case (addOneState: String, appendBangState: Int) =>
val (addOneState2, n2) = addOne(n).runState(addOneState)
val (appendBangState2, n3) = appendBang(n2.toString).runState( appendBangState)
((addOneState2, appendBangState2), n3)
}
Since I'm not quite familiar with them, just wondering is there any way to improve it. The best hope is that I can use for comprehension, but not sure if that's possible
Like I mentioned in my first comment, it will be impossible to use a for comprehension to do what you want, because it can not change the type of the state (S).
Remember that a for comprehension can be translated to a combination of flatMaps, withFilter and one map. If we look at your State.flatMap, it takes a function f to change a State[S,A] into State[S, B]. We can use flatMap and map (and thus a for comprehension) to chain together operations on the same state, but we can't change the type of the state in this chain.
We could generalize your last definition of myAction to combine, compose, ... two functions using state of a different type. We can try to implement this generalized compose method directly in our State class (although this is probably so specific, it probably doesn't belong in State). If we look at State.flatMap and myAction we can see some similarities:
We first call runState on our existing State instance.
We then call runState again
In myAction we first use the result n2 to create a State[Int, String] (AppendBang[String] or State[S2, B]) using the second function (appendBang or f) on which we then call runState. But our result n2 is of type String (A) and our function appendBang needs an Int (B) so we need a function to convert A into B.
case class State[S, A](runState: S => (S, A)) {
// flatMap and map
def compose[B, S2](f: B => State[S2, B], convert: A => B) : State[(S, S2), B] =
State( ((s: S, s2: S2) => {
val (sNext, a) = runState(s)
val (s2Next, b) = f(convert(a)).runState(s2)
((sNext, s2Next), b)
}).tupled)
}
You then could define myAction as :
def myAction(i: Int) = addOne(i).compose(appendBang, _.toString)
val twoStates = myAction(1)
// State[(String, Int),String] = State(<function1>)
twoStates.runState(("", 1))
// ((String, Int), String) = ((.,2),2 !!!)
If you don't want this function in your State class you can create it as an external function :
def combineStateFunctions[S1, S2, A, B](
a: A => State[S1, A],
b: B => State[S2, B],
convert: A => B
)(input: A): State[(S1, S2), B] = State(
((s1: S1, s2: S2) => {
val (s1Next, temp) = a(input).runState(s1)
val (s2Next, result) = b(convert(temp)).runState(s2)
((s1Next, s2Next), result)
}).tupled
)
def myAction(i: Int) =
combineStateFunctions(addOne, appendBang, (_: Int).toString)(i)
Edit : Bergi's idea to create two functions to lift a State[A, X] or a State[B, X] into a State[(A, B), X].
object State {
def onFirst[A, B, X](s: State[A, X]): State[(A, B), X] = {
val runState = (a: A, b: B) => {
val (nextA, x) = s.runState(a)
((nextA, b), x)
}
State(runState.tupled)
}
def onSecond[A, B, X](s: State[B, X]): State[(A, B), X] = {
val runState = (a: A, b: B) => {
val (nextB, x) = s.runState(b)
((a, nextB), x)
}
State(runState.tupled)
}
}
This way you can use a for comprehension, since the type of the state stays the same ((A, B)).
def myAction(i: Int) = for {
x <- State.onFirst(addOne(i))
y <- State.onSecond(appendBang(x.toString))
} yield y
myAction(1).runState(("", 1))
// ((String, Int), String) = ((.,2),2 !!!)

Type checker in trouble over #specialized

The trait below compiles fine without the #specialized annotations, or without the map method. Otherwise, it will fail with a compilation error, which doesn't make a lot of sense (at least to me):
[error] (compile:compile) scala.tools.nsc.symtab.Types$TypeError: type mismatch;
[error] found : U(in method foreach)(in method foreach)
[error] required: U(in method foreach)(in method foreach)
This is the trait that I'm talking about:
trait Tuple2Traversable[#specialized(Int, Byte) +A, #specialized(Int, Byte) +B] {
def foreach[T](fn: (A, B) => T)
def map[T](fn: (A, B) => T): Traversable[T] = new Traversable[T] {
def foreach[U](f: T => U) {
def composed(a: A, b: B) = f(fn(a, b))
Tuple2Traversable.this.foreach(composed)
}
}
def flatMap[T](fn: (A, B) => Traversable[T]): Traversable[T] = new Traversable[T] {
def foreach[U](f: (T) => U) {
def composed(a: A, b: B) = fn(a, b).foreach(f)
Tuple2Traversable.this.foreach(composed)
}
}
def filter(included: (A, B) => Boolean): Tuple2Traversable[A, B] = new Tuple2Traversable[A, B] {
def foreach[T](fn: (A, B) => T) {
def composed(a: A, b: B) = if (included(a, b)) fn(a, b)
Tuple2Traversable.this.foreach(composed)
}
}
def foldLeft[T](z: T)(fn: (T, A, B) => T): T = {
var current = z
def op(a: A, b: B) {
current = fn(current, a, b)
}
foreach(op)
current
}
def asTraversable = new Traversable[(A, B)] {
def foreach[U](f: ((A, B)) => U) {
def tupled(a: A, b: B) = f((a, b))
Tuple2Traversable.this.foreach(tupled)
}
}
}
I've been staring at this for a while now. Any suggestions on how to solve this would be highly appreciated.
Perhaps I should add that the purpose of this class is to have a Traversable of tuples, without forcing those tuples to ever be created. A Traversable[(A,B)] would accept a Tuple2[A,B] => T as the parameter of foreach. I want my 'traversable' to accept a function (A, B) => T. (Like def fn(a: Int, b: Int) = a + b.)
Looks like some internal compiler bug. I get the same error in scala 2.9.2, but it compiles fine in scala 2.10-RC2

Is it possible to implement liftM2 in Scala?

In Haskell, liftM2 can be defined as:
liftM2 :: (Monad m) => (a1 -> a2 -> r) -> m a1 -> m a2 -> m r
liftM2 f m1 m2 = do
x1 <- m1
x2 <- m2
return $ f x1 x2
I'd like to translate this to Scala. My first attempt was the following:
def liftM2[T1, T2, R, M[_]](f: (T1, T2) => R)(ma: M[T1], mb: M[T2]) : M[R] = for {
a <- ma
b <- mb
} yield f(a, b)
This fails in what I guess is the most obvious way possible: "value flatMap is not a member of type parameter M[T1]". Right, I haven't indicated that M[_] is some kind of monad. So the next thing I tried was to define some structural type like:
type Monad[A] = {
def flatMap[B](f: (A) => Monad[B]): Monad[B]
}
... and to have M[A] <: Monad[A]. But that doesn't work, because Scala doesn't have recursive structural types.
So the next few things I tried involved gyrations similar to M[A] <: FilterMonadic[A, _]. Those all failed, probably because I wasn't able to figure out the right implicit-fu for CanBuildFrom.
The most closely-related question I could find here on StackOverflow was this one, touching both on recursive structural types and how to mimic Haskell's typeclasses in Scala. But that approach requires defining an implicit conversion from each type you care about to the trait defining the typeclass, which seems terribly circular in this case...
Is there any good way to do what I'm trying to do?
The usual way to encode type classes in Scala turns out to follow Haskell pretty closely: List doesn't implement a Monad interface (as you might expect in an object-oriented language), but rather we define the type class instance in a separate object.
trait Monad[M[_]] {
def point[A](a: => A): M[A]
def bind[A, B](ma: M[A])(f: A => M[B]): M[B]
def map[A, B](ma: M[A])(f: A => B): M[B] = bind(ma)(a => point(f(a)))
}
implicit object listMonad extends Monad[List] {
def point[A](a: => A) = List(a)
def bind[A, B](ma: List[A])(f: A => List[B]) = ma flatMap f
}
This idea is introduced in Poor Man's Type Classes and explored more deeply in Type Classes as Objects and Implicits. Notice that the point method could not have been defined in an object-oriented interface, as it doesn't have M[A] as one of it's arguments to be converted to the this reference in an OO encoding. (Or put another way: it can't be part of an interface for the same reason a constructor signature can't be represented in an interface.)
You can then write liftM2 as:
def liftM2[M[_], A, B, C](f: (A, B) => C)
(implicit M: Monad[M]): (M[A], M[B]) => M[C] =
(ma, mb) => M.bind(ma)(a => M.map(mb)(b => f(a, b)))
val f = liftM2[List, Int, Int, Int](_ + _)
f(List(1, 2, 3), List(4, 5)) // List(5, 6, 6, 7, 7, 8)
This pattern has been applied extensively in Scalaz. Version 7, currently in development, includes an index of the type classes.
In addition to providing type classes and instances for standard library types, it provides a 'syntactic' layer that allows the more familiar receiver.method(args) style of method invocation. This often affords better type inference (accounting for Scala's left-to-right inference algorithm), and allows use of the for-comprehension syntactic sugar. Below, we use that to rewrite liftM2, based on the map and flatMap methods in MonadV.
// Before Scala 2.10
trait MonadV[M[_], A] {
def self: M[A]
implicit def M: Monad[M]
def flatMap[B](f: A => M[B]): M[B] = M.bind(self)(f)
def map[B](f: A => B): M[B] = M.map(self)(f)
}
implicit def ToMonadV[M[_], A](ma: M[A])
(implicit M0: Monad[M]) =
new MonadV[M, A] {
val M = M0
val self = ma
}
// Or, as of Scala 2.10
implicit class MonadOps[M[_], A](self: M[A])(implicit M: Monad[M]) {
def flatMap[B](f: A => M[B]): M[B] = M.flatMap(self)(f)
def map[B](f: A => B): M[B] = M.map(self)(f)
}
def liftM2[M[_]: Monad, A, B, C](f: (A, B) => C): (M[A], M[B]) => M[C] =
(ma, mb) => for {a <- ma; b <- mb} yield f(a, b)
Update
Yep, its possible to write less generic version of liftM2 for the Scala collections. You just have to feed in all the required CanBuildFrom instances.
scala> def liftM2[CC[X] <: TraversableLike[X, CC[X]], A, B, C]
| (f: (A, B) => C)
| (implicit ba: CanBuildFrom[CC[A], C, CC[C]], bb: CanBuildFrom[CC[B], C, CC[C]])
| : (CC[A], CC[B]) => CC[C] =
| (ca, cb) => ca.flatMap(a => cb.map(b => f(a, b)))
liftM2: [CC[X] <: scala.collection.TraversableLike[X,CC[X]], A, B, C](f: (A, B) => C)(implicit ba: scala.collection.generic.CanBuildFrom[CC[A],C,CC[C]], implicit bb: scala.collection.generic.CanBuildFrom[CC[B],C,CC[C]])(CC[A], CC[B]) => CC[C]
scala> liftM2[List, Int, Int, Int](_ + _)
res0: (List[Int], List[Int]) => List[Int] = <function2>
scala> res0(List(1, 2, 3), List(4, 5))
res1: List[Int] = List(5, 6, 6, 7, 7, 8)