I have some data which has adjacent entries that I want to group together and perform actions on.
I know roughly that fs2.Pull
can be used to "step" through a stream and do more complicated
logic than the built in combinators allow. I don't know how to write one though!
In the end we should have something like
def combineAdjacent[F[_], A](
shouldCombine: (A, A) => Boolean,
combine: (A, A) => A
): Pipe[F, A, A] =
???
The rest of this documents the steps I followed to implement the right behavior
Stream[F, A]
is a stream with effects in F
and elements in A
. Pull[F, A, R]
is a pull with effects
in F
, elements in A
, and a return value in R
. Streams are implemented in terms of Pull[F, A, Unit]
(more or less; handwaving some details). Streams are monads in A
, meaning they have
flatMap(f: A => Stream[F, B]): Stream[F, B]
.
Pull is a monad in R
, so it has flatMap(f: R => Pull[F, A, R2]): Pull[F, A, R2]
.
You might think of List's ::
(pronounced "Cons") case as "The next element, and then the rest of the list", and
Pull's uncons1
helper allows us to talk about "The next stream element, and the rest of the stream".
We will mainly be using pull's uncons1
, which lets us look at Option[(A, Stream[F, A])]
- this is very similar to using List
recursion.
Type | Operation | Result |
---|---|---|
List[A] |
match |
Nil or ::(A, List[A]) |
Stream[F, A] |
.pull.uncons1 |
Pull[F, A, Option[(A, Stream[F, A])] |
Note how we have List[A]
to (A, List[A])
vs Stream[F, A]
to Option[(A, Stream[F, A])]
We could write an uncons1
for list;
def uncons1[A](as: List[A]): Option[(A, List[A])] =
as.headOption.map(a => (a, as.tail))
With this in mind, let's solve our Pull
problem by figuring out how we'd write the equivalent option for List
First, let's write some test cases for the behavior we want to have.
describe("combineAdjacent") {
it("doesn't combine when condition is false") {
val s1 = Stream.range(0, 10)
val noCombine =
combineAdjacent[Pure, Int]((_, _) => false, null)
val s2 = s1.through(noCombine)
s2.toVector shouldEqual s1.toVector
}
it("combines when condition is true") {
val s1 = Stream(1, 3, 5, 7, 11, 13, 17, 23, 27)
val s2 = s1.flatMap(i => Stream.emits(Seq(i, i)))
val combineEqual = combineAdjacent[Pure, Int](_ == _, _ + _)
s2.through(combineEqual).toVector shouldEqual s1.map(_ * 2).toVector
}
it("combines repeatedly") {
val s1 = Stream(1, 1, 1)
val combineEqual =
combineAdjacent[Pure, Int]((_, _) => true, _ + _)
s1.through(combineEqual).toVector shouldEqual s1.foldMonoid.toVector
}
}
Now let's translate the problem from Stream to List, and the test cases.
describe("combineAdjacent for lists") {
it("doesn't combine when condition is false") {
val s1 = (0 to 10).toList
val noCombine =
combineAdjacent2[Int]((_, _) => false, null)
val s2 = noCombine(s1)
s2 shouldEqual s1
}
it("combines when condition is true") {
val s1 = List(1, 3, 5, 7, 11, 13, 17, 23, 27)
val s2 = s1.flatMap(i => List(i, i))
val combineEqual = combineAdjacent2[Int](_ == _, _ + _)
combineEqual(s2) shouldEqual s1.map(_ * 2)
}
it("combines repeatedly") {
val s1 = List(1, 1, 1)
val combineEqual = combineAdjacent2[Int]((_, _) => true, _ + _)
combineEqual(s1) shouldEqual List(s1.combineAll)
}
}
Here's my first draft at a recursive list solution to the problem, and it passes the test cases:
def combineAdjacent2[A](
shouldCombine: (A, A) => Boolean,
combine: (A, A) => A
): List[A] => List[A] = {
case Nil => Nil
case xs @ (_ :: Nil) => xs
case current :: next :: tail =>
if (shouldCombine(current, next)) {
val newLst = combine(current, next) :: tail
combineAdjacent2[A](shouldCombine, combine)(newLst)
} else
current :: combineAdjacent2[A](shouldCombine, combine)(next :: tail)
}
This works, but let's get rid of that current :: next :: tail
case, since Pull
only allows us to talk about "the next and the rest"
def combineAdjacent2[A](
shouldCombine: (A, A) => Boolean,
combine: (A, A) => A
): List[A] => List[A] = as => as match {
case Nil => Nil
case current :: rest =>
rest match {
case Nil => current :: Nil
case next :: nextTail =>
if (shouldCombine(current, next))
combineAdjacent2(shouldCombine, combine)(
combine(current, next) :: nextTail)
else
current :: combineAdjacent2(shouldCombine, combine)(rest)
}
}
Tests are still passing! 🎉
Now we can mechanically translate this, remembering that flatMapping on stream.pull.uncons1
works a lot like our recursive list match
def combineAdjacent[F[_], A](
shouldCombine: (A, A) => Boolean,
combine: (A, A) => A
): Pipe[F, A, A] = { in =>
def go(s: Stream[F, A]): Pull[F, A, Unit] =
s.pull.uncons1.flatMap {
case None => Pull.done
case Some((current, rest)) =>
rest.pull.uncons1.flatMap {
case None => Pull.output1(current)
case Some((next, nextTail)) =>
if (shouldCombine(current, next)) {
val s2 = Stream.emit(combine(current, next)) ++ nextTail
go(s2)
} else
Pull.output1(current) >> go(rest)
}
}
go(in).stream
}
List | Stream + Pull |
---|---|
match |
s.pull.uncons1.flatMap |
case Nil |
case None |
case current :: rest |
case Some((current, rest)) |
current :: <recurse>(rest) |
Pull.output1(current) >> go(rest) |
And this version passes all our tests!
Note also that the list based version is not stack safe, because it's not tail recursive.
However, the flatMap
(>>
) in Pull
is safe, because Pull/Stream is implemented with a "trampolined" construct, which gives us stack safe recursion.
While fs2 streams are purely functional, they can model side effects. We can observe a problem when the source stream we pass to combineAdjacent
is generated by effects
it("doesn't omit records when used effectfully") {
val s = Stream.range(1, 20)
// prefetchN puts the stream elements into a queue so that
// the stream from that point is non-repeatable with effects
for {
result <- s
.covary[IO]
.prefetchN(20)
.through(combineAdjacent[IO, Int]((_, _) => false, (a, _) => a))
.compile
.toVector
} yield result shouldEqual s.toVector
}
This test case will fail because of the way we've reused part of the data. Executing pull.uncons1
in our flatMap
chain had the effect of pulling data out of the stream, so there's no guarantee that the next time we get an element, it would be the same. Consider what it means to call .pull.uncons1
on a stream of Stream.repeatEval(IO(System.currentTimeMillis()))
- there's no way we'll get the same element twice.
In the case that the stream is driven by a queue, we now have a problem because we pulled two elements out. We need to fix it by re-emitting the element we just pulled out.
Fortunately we can simply state that as Pull.output1(current) >> go(Stream.emit(next) ++ nextTail)
, and the test then passes, leaving our final implementation as
def combineAdjacent[F[_], A](
shouldCombine: (A, A) => Boolean,
combine: (A, A) => A
): Pipe[F, A, A] = { in =>
def go(s: Stream[F, A]): Pull[F, A, Unit] =
s.pull.uncons1.flatMap {
case None => Pull.done
case Some((current, rest)) =>
rest.pull.uncons1.flatMap {
case None => Pull.output1(current)
case Some((next, nextTail)) =>
if (shouldCombine(current, next)) {
val s2 = Stream.emit(combine(current, next)) ++ nextTail
go(s2)
} else
Pull.output1(current) >> go(Stream.emit(next) ++ nextTail)
}
}
go(in).stream
}
In
doesn't combine when condition is false
specification it should be:instead of
Great post, thank you!