Scalaz（23）－ 泛函数据结构： Zipper-游标定位

  外面沙尘滚滚一直向北去了，意识到年关到了，码农们都回乡过年去了，而我却留在这里玩弄“拉链”。不要想歪了，我说的不是裤裆拉链而是scalaz Zipper，一种泛函数据结构游标（cursor）。在函数式编程模式里的集合通常是不可变的（immutable collection），我们会发现在FP编程过程中处理不可变集合（immutable collection）数据的方式好像总是缺些什么，比如在集合里左右逐步游动像moveNext,movePrev等等，在一个集合的中间进行添加、更新、删除的功能更是欠奉了，这主要是因为操作效率问题。不可变集合只有对前置操作（prepend operation）才能获得可靠的效率，即对集合首位元素的操作，能得到相当于O(1)的速度，其它操作基本上都是O(n)速度，n是集合的长度，也就是随着集合的长度增加，操作效率会以倍数下降。还有一个原因就是编程时会很不方便，因为大多数程序都会对各种集合进行大量的操作，最终也会导致程序的复杂臃肿，不符合函数式编程要求的精简优雅表达形式。我想可能就是因为以上各种原因，scalaz提供了Zipper typeclass帮助对不可变集合操作的编程。Zipper的定义如下：scalaz/Zipper.scala

final case class Zipper[+A](lefts: Stream[A], focus: A, rights: Stream[A])

它以Stream为基础，A可以是任何类型，无论基础类型或高阶类型。Zipper的结构如上：当前焦点窗口、左边一串数据元素、右边一串，形似拉链，因而命名Zipper。或者这样看会更形象一点：

final case class Zipper[+A]( lefts: Stream[A], focus: A, rights: Stream[A])

scalaz提供了Zipper构建函数可以直接用Stream生成一个Zipper:

trait StreamFunctions { ... final def toZipper[A](as: Stream[A]): Option[Zipper[A]] = as match { case Empty   => None case h #:: t => Some(Zipper.zipper(empty, h, t)) } final def zipperEnd[A](as: Stream[A]): Option[Zipper[A]] = as match { case Empty => None case _     => val x = as.reverse Some(Zipper.zipper(x.tail, x.head, empty)) } ...

zipperEnd生成倒排序的Zipper:

1   Stream(1,2,3).toZipper                          //> res2: Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 1, <rights>))
2   Stream("A","B","C").toZipper                    //> res3: Option[scalaz.Zipper[String]] = Some(Zipper(<lefts>, A, <rights>))
3   Stream(Stream(1,2),Stream(3,4)).toZipper        //> res4: Option[scalaz.Zipper[scala.collection.immutable.Stream[Int]]] = Some(Z 4                                                   //| ipper(<lefts>, Stream(1, ?), <rights>))
5   Stream(1,2,3).zipperEnd                         //> res5: Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 3, <rights>))

scalaz也为List，NonEmptyList提供了Zipper构建函数：

trait ListFunctions { ... final def toZipper[A](as: List[A]): Option[Zipper[A]] = stream.toZipper(as.toStream) final def zipperEnd[A](as: List[A]): Option[Zipper[A]] = stream.zipperEnd(as.toStream) ... final class NonEmptyList[+A] private[scalaz](val head: A, val tail: List[A]) { ... def toZipper: Zipper[A] = zipper(Stream.Empty, head, tail.toStream) def zipperEnd: Zipper[A] = { import Stream._ tail.reverse match { case Nil     => zipper(empty, head, empty) case t :: ts => zipper(ts.toStream :+ head, t, empty) } } ...

都是先转换成Stream再生成Zipper的。Zipper本身的构建函数是zipper，在NonEmptyList的Zipper生成中调用过：

trait ZipperFunctions { def zipper[A](ls: Stream[A], a: A, rs: Stream[A]): Zipper[A] = Zipper(ls, a, rs) }

用这些串形结构的构建函数产生Zipper同样很简单：

1 List(1,2,3,4).toZipper                          //> res0: Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 1, <rights>))
2   List(List(1,2),List(2,3)).toZipper              //> res1: Option[scalaz.Zipper[List[Int]]] = Some(Zipper(<lefts>, List(1, 2), <r 3                                                   //| ights>))
4   NonEmptyList("A","C","E").toZipper              //> res2: scalaz.Zipper[String] = Zipper(<lefts>, A, <rights>)
5   NonEmptyList(1,2,3).zipperEnd                   //> res3: scalaz.Zipper[Int] = Zipper(<lefts>, 3, <rights>)
6  

有了串形集合的Zipper构建方法后我们再看看一下Zipper的左右游动函数：

final case class Zipper[+A](lefts: Stream[A], focus: A, rights: Stream[A]) { ... /** * Possibly moves to next element to the right of focus. */ def next: Option[Zipper[A]] = rights match { case Stream.Empty => None case r #:: rs     => Some(zipper(Stream.cons(focus, lefts), r, rs)) } /** * Possibly moves to next element to the right of focus. */ def nextOr[AA >: A](z: => Zipper[AA]): Zipper[AA] = next getOrElse z /** * Possibly moves to the previous element to the left of focus. */ def previous: Option[Zipper[A]] = lefts match { case Stream.Empty => None case l #:: ls     => Some(zipper(ls, l, Stream.cons(focus, rights))) } /** * Possibly moves to previous element to the left of focus. */ def previousOr[AA >: A](z: => Zipper[AA]): Zipper[AA] = previous getOrElse z /** * Moves focus n elements in the zipper, or None if there is no such element. * * @param n number of elements to move (positive is forward, negative is backwards) */ def move(n: Int): Option[Zipper[A]] = { @tailrec def move0(z: Option[Zipper[A]], n: Int): Option[Zipper[A]] =
      if (n > 0 && rights.isEmpty || n < 0 && lefts.isEmpty) None else { if (n == 0) z else if (n > 0) move0(z flatMap ((_: Zipper[A]).next), n - 1) else move0(z flatMap ((_: Zipper[A]).previous), n + 1) } move0(Some(this), n) } /** * Moves focus to the start of the zipper. */ def start: Zipper[A] = { val rights = this.lefts.reverse ++ focus #:: this.rights this.copy(Stream.Empty, rights.head, rights.tail) } /** * Moves focus to the end of the zipper. */ def end: Zipper[A] = { val lefts = this.rights.reverse ++ focus #:: this.lefts this.copy(lefts.tail, lefts.head, Stream.empty) } /** * Moves focus to the nth element of the zipper, or the default if there is no such element. */ def moveOr[AA >: A](n: Int, z: => Zipper[AA]): Zipper[AA] = move(n) getOrElse z ...

start,end,move,next,previous移动方式都齐了。还有定位函数：

... /** * Moves focus to the nearest element matching the given predicate, preferring the left, * or None if no element matches. */ def findZ(p: A => Boolean): Option[Zipper[A]] =
    if (p(focus)) Some(this) else { val c = this.positions std.stream.interleave(c.lefts, c.rights).find((x => p(x.focus))) } /** * Moves focus to the nearest element matching the given predicate, preferring the left, * or the default if no element matches. */ def findZor[AA >: A](p: A => Boolean, z: => Zipper[AA]): Zipper[AA] = findZ(p) getOrElse z /** * Given a traversal function, find the first element along the traversal that matches a given predicate. */ def findBy[AA >: A](f: Zipper[AA] => Option[Zipper[AA]])(p: AA => Boolean): Option[Zipper[AA]] = { @tailrec def go(zopt: Option[Zipper[AA]]): Option[Zipper[AA]] = { zopt match { case Some(z) => if (p(z.focus)) Some(z) else go(f(z)) case None    => None } } go(f(this)) } /** * Moves focus to the nearest element on the right that matches the given predicate, * or None if there is no such element. */ def findNext(p: A => Boolean): Option[Zipper[A]] = findBy((z: Zipper[A]) => z.next)(p) /** * Moves focus to the previous element on the left that matches the given predicate, * or None if there is no such element. */ def findPrevious(p: A => Boolean): Option[Zipper[A]] = findBy((z: Zipper[A]) => z.previous)(p) ...

操作函数如下：

... /** * An alias for insertRight */ def insert[AA >: A]: (AA => Zipper[AA]) = insertRight(_: AA) /** * Inserts an element to the left of focus and focuses on the new element. */ def insertLeft[AA >: A](y: AA): Zipper[AA] = zipper(lefts, y, focus #:: rights) /** * Inserts an element to the right of focus and focuses on the new element. */ def insertRight[AA >: A](y: AA): Zipper[AA] = zipper(focus #:: lefts, y, rights) /** * An alias for `deleteRight` */ def delete: Option[Zipper[A]] = deleteRight /** * Deletes the element at focus and moves the focus to the left. If there is no element on the left, * focus is moved to the right. */ def deleteLeft: Option[Zipper[A]] = lefts match { case l #:: ls     => Some(zipper(ls, l, rights)) case Stream.Empty => rights match { case r #:: rs     => Some(zipper(Stream.empty, r, rs)) case Stream.Empty => None } } /** * Deletes the element at focus and moves the focus to the left. If there is no element on the left, * focus is moved to the right. */ def deleteLeftOr[AA >: A](z: => Zipper[AA]): Zipper[AA] = deleteLeft getOrElse z /** * Deletes the element at focus and moves the focus to the right. If there is no element on the right, * focus is moved to the left. */ def deleteRight: Option[Zipper[A]] = rights match { case r #:: rs     => Some(zipper(lefts, r, rs)) case Stream.Empty => lefts match { case l #:: ls     => Some(zipper(ls, l, Stream.empty)) case Stream.Empty => None } } /** * Deletes the element at focus and moves the focus to the right. If there is no element on the right, * focus is moved to the left. */ def deleteRightOr[AA >: A](z: => Zipper[AA]): Zipper[AA] = deleteRight getOrElse z /** * Deletes all elements except the focused element. */ def deleteOthers: Zipper[A] = zipper(Stream.Empty, focus, Stream.Empty) ... /** * Update the focus in this zipper. */ def update[AA >: A](focus: AA) = { this.copy(this.lefts, focus, this.rights) } /** * Apply f to the focus and update with the result. */ def modify[AA >: A](f: A => AA) = this.update(f(this.focus)) ...

insert,modify,delete也很齐备。值得注意的是多数Zipper的移动函数和操作函数都返回Option[Zipper[A]]类型，如此我们可以用flatMap把这些动作都连接起来。换句话说就是我们可以用for-comprehension在Option的context内实现行令编程（imperative programming）。我们可以通过一些例子来示范Zipper用法：

 1 val zv = for {  2     z <- List(2,8,1,5,4,11).toZipper  3     s1 <- z.next  4     s2 <- s1.modify{_ + 2}.some  5   } yield s2                                      //> zv : Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 10, <rights>))
 6   
 7   zv.get.show          //> res8: scalaz.Cord = Zipper(Stream(2), 10, Stream(1,5,4,11))
 8   zv.get.toList        //> res9: List[Int] = List(2, 10, 1, 5, 4, 11)
 9 ... 10 val zv = for { 11     z <- List(2,8,1,5,4,11).toZipper 12     s1 <- z.next 13     s2 <- s1.modify{_ + 2}.some 14     s3 <- s2.move(1) 15     s4 <- s3.delete 16   } yield s4                                      //> zv : Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 5, <rights>))
17   
18   zv.get.show       //> res8: scalaz.Cord = Zipper(Stream(10,2), 5, Stream(4,11))
19   zv.get.toList     //> res9: List[Int] = List(2, 10, 5, 4, 11)
20 ... 21 val zv = for { 22     z <- List(2,8,1,5,4,11).toZipper 23     s1 <- z.next 24     s2 <- s1.modify{_ + 2}.some 25     s3 <- s2.move(1) 26     s4 <- s3.delete 27     s5 <- s4.findZ {_ === 11} 28     s6 <- if (s5.focus === 12) s5.delete else s2.insert(12).some 29   } yield s6                                      //> zv : Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 12, <rights>))
30   
31   zv.get.show        //> res8: scalaz.Cord = Zipper(Stream(10,2), 12, Stream(1,5,4,11))
32   zv.get.toList      //> res9: List[Int] = List(2, 10, 12, 1, 5, 4, 11)
33 ... 34 val zv = for { 35     z <- List(2,8,1,5,4,11).toZipper 36     s1 <- z.next 37     s2 <- s1.modify{_ + 2}.some 38     s3 <- s2.move(1) 39     s4 <- s3.delete 40     s5 <- s4.findZ {_ === 11} 41     s6 <- if (s5.focus === 12) s5.delete else s2.insert(12).some 42     s7 <- s6.end.delete 43     s8 <- s7.start.some 44   } yield s8                                      //> zv : Option[scalaz.Zipper[Int]] = Some(Zipper(<lefts>, 2, <rights>))
45   
46   zv.get.show         //> res8: scalaz.Cord = Zipper(Stream(), 2, Stream(10,12,1,5,4))
47   zv.get.toList       //> res9: List[Int] = List(2, 10, 12, 1, 5, 4)

我在上面的程序里在for{...}yield里面逐条添加指令从而示范游标当前焦点和集合元素跟随着的变化。这段程序可以说就是一段行令程序。
回到上面提到的效率和代码质量讨论。我们提过scalaz提供Zipper就是为了使集合操作编程更简明优雅，实际情况是怎样的呢？

举个例子：有一串数字，比如：List(1,4,7,9,5,6,10), 我想找出第一个高点元素，它的左边低，右边高，在我们的例子里是元素9。如果我们尝试用习惯的行令方式用索引去编写这个函数：

def peak(list: List[Int]): Option[Int] = { list.indices.find { index => val x = list(index) index > 0 && index < list.size - 1 && x > list(index - 1) && x > list(index + 1) }.map(list(_)) }

哇！这东西不但极其复杂难懂而且效率低下，重复用find索引导致速度降到O(n * n)。如果用Array会把效率提高到O(n),不过我们希望用immutable方式。那么用函数式编程方式呢？

def peak_fp(list: List[Int]): Option[Int] = list match { case x :: y :: z :: tl if y > x && y > z => Some(y) case x :: tl => peak(tl) case Nil => None } 

用模式匹配（pattern matching）和递归算法（recursion），这段程序好看多了，而且效率也可以提高到O(n)。

但我们再把情况搞得复杂一点：把高点值增高一点（+1）。还是用FP方式编写：

def raisePeak(list: List[Int]): Option[List[Int]] = { def rec(head: List[Int], tail: List[Int]): Option[List[Int]] = tail match { case x :: y :: z :: tl if y > x && y > z => Some((x :: head).reverse ::: ((y +1) :: z :: tl)) case x :: tl => rec(x :: head, tl) case Nil => None } rec(List.empty, list) }

代码又变得臃肿复杂起来。看来仅仅用FP编程方式还不足够，还需要用一些新的数据结构什么的来帮助。scalaz的Zipper可以在这个场景里派上用场了：

def raisePeak_z(list: List[Int]): Option[List[Int]] = { for { zipper <- list.toZipper peak <- zipper.positions.findNext( z => (z.previous, z.next) match { case (Some(p), Some(n)) => p.focus < z.focus && n.focus < z.focus case _ => false }) } yield (peak.focus.modify(_ + 1).toStream.toList) }

用Zipper来写程序表达清楚许多。这里用上了Zipper.positions：

/** * A zipper of all positions of the zipper, with focus on the current position. */ def positions: Zipper[Zipper[A]] = { val left = std.stream.unfold(this)(_.previous.map(x => (x, x))) val right = std.stream.unfold(this)(_.next.map(x => (x, x))) zipper(left, this, right) }

positions函数返回类型是Zipper[Zipper[A]]符合findNext使用。我们前面已经提到：使用Zipper的成本约为O(n)。