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transducers tic-tac
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gistfile1.scala
//--
// Clojure's Transducers
// (the simpler parts)
//--
// References:
// Transducers by Rich Hickey on youtube
// There are also scala implementations in existence:
// (which are differently implemented from what we do here)
// https://github.com/knutwalker/transducers-scala
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
val result =
input
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt)
//--
// we've implemented
def f(xs: List[String]): List[Int]
// +
// its composable
// direct for this use-case
// -
// needlessly specific
// allocates a new container every time.
//--
// approach 1:
// Iterator => Iterator
//--
def f(xs: Iterator[String]): Iterator[Int] =
xs
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt)
//--
// build a driver
def run[A, B, F[_] <: Iterable[_]](
xs: F[A], f: Iterator[A] => Iterator[B]): F[B]
//--
// oh, right its not that simple :)
//--
import scala.collection.generic.CanBuildFrom
def run[A, F[I] <: Iterable[I], B, That](
xs: F[A],
f: Iterator[A] => Iterator[B])(
implicit cbf: CanBuildFrom[F[A],B,That]): That
//--
// build a driver
def run[A, F[I] <: Iterable[I], B, That](
xs: F[A],
f: Iterator[A] => Iterator[B])(
implicit cbf: CanBuildFrom[F[A],B,That]): That = {
val bIter: Iterator[B] = f(xs.iterator)
val builder = cbf(xs)
bIter.foreach{ builder += _ }
builder.result
}
//--
// build a driver
def run[A, F[I] <: Iterable[I], B, That](
xs: F[A],
f: Iterator[A] => Iterator[B])(
implicit cbf: CanBuildFrom[F[A],B,That]): That = {
...
}
run(List("1,2", "3,4,5", "NA", "6", "NA"), f)
// result: List(1, 2, 3, 4, 5, 6)
//--
// approach 1:
// Process = Iterator => Iterator
// +
// familiar
// composeable
// no extra allocations
//--
// approach 1:
// Process[A,B] = Iterator[A] => Iterator[B]
// +
// familiar
// composeable
// no extra allocations
// -
// unusable on real-time streams.
//--
// a real time stream is not an iterator
realTimeStream.hasNext // maybe, maybe not?
//--
// let's look at it one input at a time.
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
//--
// let's look at it one input at a time.
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
// we can describe this transformation with:
def f(x: String): Iterator[Int]
//--
// approach 2:
// Process[A,B] = A => Iterator[B]
trait Transformer[-A,+B]
extends Function1[A,Iterator[B]]
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
val process: Transformer[String,Int] =
filter[String](_ != "NA") andThen
mapCat[String, String](_.split(",")) andThen
map(_.toInt)
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
val process: Transformer[String,Int] =
filter[String](_ != "NA") andThen
mapCat[String, String](_.split(",")) andThen
map(_.toInt)
input.flatMap(process)
// result: List(1, 2, 3, 4, 5, 6)
//--
// the only difference between Transformer[A,B]
// & regular A => Iterator[B]
// is convenience for composition
val first: A => Iterator[B]
val second: B => Iterator[C]
// want
val sequenced: A => Iterator[C]
//--
trait Transformer[-A,+B]
extends Function1[A,Iterator[B]] { self =>
def andThen[C](next: Transformer[B,C]): Transformer[A,C] =
new Transformer[A,C] {
def apply(a: A): Iterator[C] =
self.apply(a).flatMap(next)
}
}
//--
def map[A,B](f: A => B): Transformer[A,B] =
new Transformer[A,B] {
def apply(a:A) = Iterator(f(a))
}
//--
def filter[A](f: A => Boolean): Transformer[A,A] =
new Transformer[A,A] {
def apply(a:A) = Iterator(a).filter(f)
}
//--
def mapCat[A,B](f: A => TraversableOnce[B]): Transformer[A,B] =
new Transformer[A,B] {
def apply(a:A) = f(a).toIterator
}
//--
// approach 2:
// Transformer[A,B] = A => Iterator[B]
// +
// fairly familiar
// composeable
// highly generic
// -
//--
// approach 2:
// Transformer[A,B] = A => Iterator[B]
// +
// fairly familiar
// composeable
// generic
// -
// allocations!!
//--
// Transformer[A,B] = A => Iterator[B]
// -
// allocations!!
filter[String](_ != "NA") andThen
mapCat[String, String](_.split(",")) andThen
map(_.toInt)
//--
// Clojure's transducers
// +
// fairly familiar
// composeable
// generic
// no extra allocations
//--
// Let's add a step to the problem.
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = List(1,2,3,4,5,6)
//--
// Let's add a step to the problem.
val input = List("1,2", "3,4,5", "NA", "6", "NA")
// val expectedResult = List(1,2,3,4,5,6)
val expectedResult = 1 + 2 + 3 + 4 + 5 + 6
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
// val expectedResult = List(1,2,3,4,5,6)
val expectedResult = 1 + 2 + 3 + 4 + 5 + 6 // 21
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val expectedResult = 1 + 2 + 3 + 4 + 5 + 6 // 21
val result =
input
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt) // List[Int]
.foldLeft(0)(_ + _) // 21
//--
def useInt(soFar: Int, elem: Int): Int = soFar + elem
input
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt) // List[Int]
.foldLeft(0)(useInt) // 21
//--
def useStringInt(soFar: Int, strInt: String): Int =
soFar + strInt.toInt
input
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt) // List[Int]
.foldLeft(0)(useInt) // 21
//--
def useStringInt(soFar: Int, strInt: String): Int =
soFar + strInt.toInt
input
.filter(_ != "NA")
.flatMap(_.split(",")) // List[String]
.foldLeft(0)(useStringInt) // 21
//--
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
strInt.split(",").foldLeft(soFar)(_ + _)
input
.filter(_ != "NA")
.flatMap(_.split(",")) // List[String]
.foldLeft(0)(useStringInt) // 21
//--
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
input
.filter(_ != "NA") // List[String]
.foldLeft(0)(useCSVStringInt) // 21
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
str match {
case "NA" => soFar
case csvStrInt => csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
}
input
.filter(_ != "NA") // List[String]
.foldLeft(0)(useCSVStringInt) // 21
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
str match {
case "NA" => soFar
case csvStrInt => csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
}
input
.foldLeft(0)(useNullableCSVStringInt) // 21
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
str match {
case "NA" => soFar
case csvStrInt => csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
}
input
.foldLeft(0)(useNullableCSVStringInt) // 21
input
.filter(_ != "NA")
.flatMap(_.split(","))
.map(_.toInt)
.foldLeft(0)(useInt) // 21
//--
// surely we can do better than this.
def useNullableCSVStringInt(soFar: Int, str: String): Int =
str match {
case "NA" => soFar
case csvStrInt => csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
}
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
def useStringInt(soFar: Int, strInt: String): Int =
soFar + strInt.toInt
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useStringInt(soFar: Int, strInt: String): Int =
soFar + strInt.toInt
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(useStringInt)
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
str match {
case "NA" => soFar
case csvStrInt => csvStrInt.split(",").foldLeft(soFar)(_ + _.toInt)
}
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(useStringInt)
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
if (str != "NA") useCSVStringInt(soFar, str) else soFar
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(useStringInt)
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
if (str != "NA") useCSVStringInt(soFar, str) else soFar
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(useStringInt)
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
def useInt(soFar: Int, elem: Int): Int = soFar + elem
//--
// let's generalize
def useInt(soFar: R, elem: Int): R
//--
def useStringInt(soFar: R, elem: String): R = ???
def useInt(soFar: R, elem: Int): R
//--
def useStringInt(soFar: R, elem: String): R = {
val f: String => Int = _.toInt
useInt(soFar, f(elem))
}
def useInt(soFar: R, elem: Int): R
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
def useStringIntF: (Int,String) => Int =
map[String, Int, Int](_.toInt)(useInt(_,_))
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
def useStringIntF: (Int,String) => Int =
map[String, Int, Int](_.toInt)(useInt(_,_))
useStringIntF(1,"30") // 31
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
class MappingTransducer[A,B](f: A => B) {
...
}
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
class MappingTransducer[A,B](f: A => B) {
def apply[R](useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
}
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
class MappingTransducer[A,B](f: A => B) {
def apply[R](useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
}
val mapStringToInt = new MappingTransducer[String, Int](_.toInt)
//--
def map[A,B,R](f: A => B)(useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
class MappingTransducer[A,B](f: A => B) {
def apply[R](useB: (R,B) => R): (R,A) => R =
(r,a) => useB(r, f(a))
}
val mapStringToInt = new MappingTransducer[String, Int](_.toInt)
def useStringIntF: (Int,String) => Int =
mapStringToInt.apply(useInt(_,_))
useStringIntF(1,"30") // 31
//--
def useNullableCSVStringInt(soFar: Int, str: String): Int =
if (str != "NA") useCSVStringInt(soFar, str) else soFar
def useCSVStringInt(soFar: Int, csvStrInt: String): Int
//--
def filter[A,R](f: A => Boolean)(useA: (R,A) => R): (R,A) => R =
(r,a) => if (f(a)) useA(r, a) else r
//--
class FilteringTransducer[A](f: A => Boolean) {
def apply[R](useA: (R,A) => R): (R,A) => R =
(r,a) => if (f(a)) useA(r, a) else r
}
// alternative in approach 2: allocations!!
//--
trait Transducer[A,B] {
def apply[R](useB: (R,B) => R): (R,A) => R
}
// give me a consumer of Bs
// I'll give you a consumer of As.
//--
trait Transducer[A,B] {
def apply[R](useB: (R,B) => R): (R,A) => R
}
def useNullableCSVStringInt(soFar: Int, str: String): Int =
if (str != "NA") useCSVStringInt(soFar, str) else soFar
// ^^ Filtering Transducer
def useCSVStringInt(soFar: Int, csvStrInt: String): Int =
csvStrInt.split(",").foldLeft(soFar)(useStringInt)
// ^^ MapCatting Transducer
def useStringInt(soFar: Int, strInt: String): Int =
useInt(soFar, strInt.toInt)
// ^^ Map Transducer
def useInt(soFar: Int, elem: Int): toInt = soFar + elem
//--
trait Transducer[A,B] {
def apply[R](useB: (R,B) => R): (R,A) => R
def andThen[C](next: Transducer[B,C]): Transducer[A,C]
// I can transform a consumer of Bs to a consumer of As
// you can transform a consumer of Cs to a consumer of Bs
// let's work together.
}
//--
trait Transducer[A,B] {
def apply[R](useB: (R,B) => R): (R,A) => R
def andThen[C](next: Transducer[B,C]): Transducer[A,C] =
// I can transform a consumer of Bs to a consumer of As
// you can transform a consumer of Cs to a consumer of Bs
// let's work together.
new Transducer[A,C] {
def apply[R](step: (R,C) => R): (R,A) => R = {
val bStep = next.apply(step)
self.apply(bStep)
}
}
}
//--
def map[A,B](f: A => B): Transducer[A,B] =
new Transducer[A,B] {
def apply[R](step: (R,B) => R): (R,A) => R =
(r,a) => step(r, f(a))
}
//--
def map[A,B](f: A => B): Transducer[A,B] =
new Transducer[A,B] {
def apply[R](step: (R,B) => R): (R,A) => R =
(r,a) => step(r, f(a))
}
def filter[A](f: A => Boolean): Transducer[A,A] =
new Transducer[A, A] {
def apply[R](step: (R,A) => R): (R,A) => R =
(r,a) => if (f(a)) step(r,a) else r
}
//--
def map[A,B](f: A => B): Transducer[A,B] =
new Transducer[A,B] {
def apply[R](step: (R,B) => R): (R,A) => R =
(r,a) => step(r, f(a))
}
def filter[A](f: A => Boolean): Transducer[A,A] =
new Transducer[A, A] {
def apply[R](step: (R,A) => R): (R,A) => R =
(r,a) => if (f(a)) step(r,a) else r
}
def mapCat[A,B](f: A => TraversableOnce[B]): Transducer[A,B] =
new Transducer[A,B] {
def apply[R](step: (R,B) => R): (R,A) => R =
(r,a) => f(a).foldLeft(r)(step)
}
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val process: Transducer[String, Int] =
filter[String](_ != "NA") andThen
mapCat(_.split(",")) andThen
map(_.toInt)
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val process: Transducer[String, Int] =
filter[String](_ != "NA") andThen
mapCat(_.split(",")) andThen
map(_.toInt)
def sum(xs: List[String]): Int =
xs.foldLeft(0)(process.apply(_ + _))
// sum(input) = 21
//--
val input = List("1,2", "3,4,5", "NA", "6", "NA")
val process: Transducer[String, Int] =
filter[String](_ != "NA") andThen
mapCat(_.split(",")) andThen
map(_.toInt)
def build(xs: List[String]): Vector[Int] =
xs.foldLeft(Vector.empty[Int])(process.apply(_ :+ _))
// build(input) = Vector(1, 2, 3, 4, 5, 6)
//--
// Clojure's transducers
// +
// composeable
// ultra generic
// no extra allocations
// -
// programming them is tough (contraMap)
//--
// Clojure's transducers
// +
// composeable
// ultra generic
// no extra allocations
// -
// programming them is tough (contraMap)
// stateful processes are tricky to write and use.
//--
val have = List(1,10,2,20,3,30,4)
val want = Vector(11, 22, 33) // pair consecutive and sum, drop unpaired end.
//--
val have = List(1,10,2,20,3,30,4)
val want = Vector(11, 22, 33) // pair consecutive and sum, drop unpaired end.
def pair[A]: Transducer[A,(A,A)] =
new Transducer[A, (A,A)] {
def apply[R](step: (R,(A,A)) => R): (R,A) => R = ???
}
//--
def pair[A]: Transducer[A,(A,A)] =
new Transducer[A, (A,A)] {
def apply[R](step: (R,(A,A)) => R): (R,A) => R = {
var cache: Option[A] = None // say hello to my mutable state
(r,a) => cache match {
case Some(a1) =>
cache = None
step(r, (a1, a))
case None =>
cache = Some(a)
r
}
}
}
//--
val process =
pair[Int] andThen
map { xs => (xs._1 + xs._2) }
def run(xs: List[Int]): Vector[Int] =
xs.foldLeft(Vector[Int]())(process(_ :+ _))
val have = List(1,10,2,20,3,33,4)
run(have) // Vector(11, 22, 36)
run(have) // Vector(11, 22, 36)
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