什么是 Scala 延续以及为什么使用它们?

发布于 2024-08-06 10:46:56 字数 1212 浏览 12 评论 0原文

我刚刚完成Scala 编程,并且我一直在研究Scala 2.7 和 2.8 之间的变化。似乎最重要的是 Continuations 插件,但我不明白它有什么用处或它是如何工作的。我发现它对于异步 I/O 有好处,但我一直无法找出原因。关于该主题的一些更受欢迎的资源如下:

StackOverflow 上的这个问题:

不幸的是,这些参考文献都没有尝试定义延续的用途或移位/重置函数应该做什么,而且我还没有找到任何这样做的参考文献。我无法猜测链接文章中的任何示例如何工作(或它们的作用),因此帮助我的一种方法可能是逐行浏览其中一个示例。即使是第三篇文章中的这个简单的问题:

reset {
    ...
    shift { k: (Int=>Int) =>  // The continuation k will be the '_ + 1' below.
        k(7)
    } + 1
}
// Result: 8

为什么结果是 8?这可能会帮助我开始。

I just finished Programming in Scala, and I've been looking into the changes between Scala 2.7 and 2.8. The one that seems to be the most important is the continuations plugin, but I don't understand what it's useful for or how it works. I've seen that it's good for asynchronous I/O, but I haven't been able to find out why. Some of the more popular resources on the subject are these:

And this question on Stack Overflow:

Unfortunately, none of these references try to define what continuations are for or what the shift/reset functions are supposed to do, and I haven't found any references that do. I haven't been able to guess how any of the examples in the linked articles work (or what they do), so one way to help me out could be to go line-by-line through one of those samples. Even this simple one from the third article:

reset {
    ...
    shift { k: (Int=>Int) =>  // The continuation k will be the '_ + 1' below.
        k(7)
    } + 1
}
// Result: 8

Why is the result 8? That would probably help me to get started.

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萌化 2024-08-13 10:46:56

我的博客确实解释了重置 和 shift 会执行此操作,因此您可能需要再次阅读该内容。

另一个很好的来源(我也在我的博客中指出)是关于连续传递样式的维基百科条目。到目前为止,这个是关于这个主题最清晰的,尽管它不使用 Scala 语法,并且延续是显式传递的。

关于定界延续的论文(我在博客中链接到该论文但似乎已损坏)给出了许多用法示例。

但我认为分隔延续概念的最好例子是 Scala Swarm。在其中,库停止代码在某一时刻的执行,而剩余的计算则成为继续。然后,库会执行某些操作 - 在本例中,将计算传输到另一台主机,并将结果(所访问的变量的值)返回到已停止的计算。

现在,您甚至不理解 Scala 页面上的简单示例,所以请阅读我的博客。在其中,我关心解释这些基础知识,以及为什么结果是8

My blog does explain what reset and shift do, so you may want to read that again.

Another good source, which I also point in my blog, is the Wikipedia entry on continuation passing style. That one is, by far, the most clear on the subject, though it does not use Scala syntax, and the continuation is explicitly passed.

The paper on delimited continuations, which I link to in my blog but seems to have become broken, gives many examples of usage.

But I think the best example of the concept of delimited continuations is Scala Swarm. In it, the library stops the execution of your code at one point, and the remaining computation becomes the continuation. The library then does something -- in this case, transferring the computation to another host, and returns the result (the value of the variable which was accessed) to the computation that was stopped.

Now, you don't understand even the simple example on the Scala page, so do read my blog. In it I'm only concerned with explaining these basics, of why the result is 8.

鼻尖触碰 2024-08-13 10:46:56

我发现现有的解释在解释这个概念方面不如我希望的那么有效。我希望这一点是清楚的(并且正确的)。我还没有使用过延续。

当调用延续函数 cf 时:

  1. 执行会跳过 shift 块的其余部分,并在其末尾再次开始
    • 传递给 cf 的参数是 shift 块在执行继续时“评估”的结果。每次调用 cf
    • 时,这可能会有所不同

  2. 执行将继续,直到 reset 块结束(或者直到调用 reset,如果没有堵塞)
    • reset 块的结果(如果没有块,则为 reset() 的参数)是 cf 返回的内容李>
  3. 结果 直到 shift 块结束
  4. 执行会跳过,直到 reset 块结束(或者调用重置?)

cf 之后继续, 在此示例中,按照从 A 到 Z 的字母

reset {
  // A
  shift { cf: (Int=>Int) =>
    // B
    val eleven = cf(10)
    // E
    println(eleven)
    val oneHundredOne = cf(100)
    // H
    println(oneHundredOne)
    oneHundredOne
  }
  // C execution continues here with the 10 as the context
  // F execution continues here with 100
  + 1
  // D 10.+(1) has been executed - 11 is returned from cf which gets assigned to eleven
  // G 100.+(1) has been executed and 101 is returned and assigned to oneHundredOne
}
// I

打印:

11
101

I found the existing explanations to be less effective at explaining the concept than I would hope. I hope this one is clear (and correct.) I have not used continuations yet.

When a continuation function cf is called:

  1. Execution skips over the rest of the shift block and begins again at the end of it
    • the parameter passed to cf is what the shift block "evaluates" to as execution continues. this can be different for every call to cf
  2. Execution continues until the end of the reset block (or until a call to reset if there is no block)
    • the result of the reset block (or the parameter to reset() if there is no block) is what cf returns
  3. Execution continues after cf until the end of the shift block
  4. Execution skips until the end of the reset block (or a call to reset?)

So in this example, follow the letters from A to Z

reset {
  // A
  shift { cf: (Int=>Int) =>
    // B
    val eleven = cf(10)
    // E
    println(eleven)
    val oneHundredOne = cf(100)
    // H
    println(oneHundredOne)
    oneHundredOne
  }
  // C execution continues here with the 10 as the context
  // F execution continues here with 100
  + 1
  // D 10.+(1) has been executed - 11 is returned from cf which gets assigned to eleven
  // G 100.+(1) has been executed and 101 is returned and assigned to oneHundredOne
}
// I

This prints:

11
101
紅太極 2024-08-13 10:46:56

给出研究论文中关于 Scala 分隔延续的典型示例,稍加修改,使 shift 的函数输入被命名为 f,因此不再是匿名的。

def f(k: Int => Int): Int = k(k(k(7)))
reset(
  shift(f) + 1   // replace from here down with `f(k)` and move to `k`
) * 2

Scala 插件转换此示例,使得从每次 shift 到调用 reset 的计算(在 reset 的输入参数内)为 < em>替换为shift输入的函数(例如f)。

替换的计算转移(即移动)到函数k中。函数f输入函数k,其中k包含替换的计算,k > 输入x: Intk中的计算将shift(f)替换为x

f(k) * 2
def k(x: Int): Int = x + 1

其效果与以下内容相同:

k(k(k(7))) * 2
def k(x: Int): Int = x + 1

注意输入参数 x 的类型 Int(即 k 的类型签名)由类型给出f 输入参数的签名。

另一个 借用 具有概念上等效抽象的示例,即 readshift 的函数输入:

def read(callback: Byte => Unit): Unit = myCallback = callback
reset {
  val byte = "byte"

  val byte1 = shift(read)   // replace from here with `read(callback)` and move to `callback`
  println(byte + "1 = " + byte1)
  val byte2 = shift(read)   // replace from here with `read(callback)` and move to `callback`
  println(byte + "2 = " + byte2)
}

我相信这将被翻译为逻辑上的等价物:

val byte = "byte"

read(callback)
def callback(x: Byte): Unit {
  val byte1 = x
  println(byte + "1 = " + byte1)
  read(callback2)
  def callback2(x: Byte): Unit {
    val byte2 = x
    println(byte + "2 = " + byte1)
  }
}

我希望这阐明了连贯的公共抽象,而先前的这两个示例的演示在某种程度上使该抽象变得模糊不清。例如,规范的第一个示例在研究论文 作为一个匿名函数,而不是我命名的 f,因此一些读者并不能立即清楚它抽象地类似于 借用第二个示例。

因此,分隔的延续创造了一种控制反转的错觉,从“你从 reset 外部呼叫我”到“我在 reset 内部呼叫你”。

注意f的返回类型是,而k不是,要求与reset的返回类型相同,即f 可以自由地为 k 声明任何返回类型,只要 f 返回与 reset 相同的类型。 读取捕获也是如此(另请参阅下面的ENV)。


分隔延续不会隐式反转状态控制,例如,read 和callback 不是纯函数。因此,调用者无法创建引用透明的表达式,因此无法对预期的命令进行声明式(也称为透明)控制语义。

我们可以显式地实现带有分隔延续的纯函数。

def aread(env: ENV): Tuple2[Byte,ENV] {
  def read(callback: Tuple2[Byte,ENV] => ENV): ENV = env.myCallback(callback)
  shift(read)
}
def pure(val env: ENV): ENV {
  reset {
    val (byte1, env) = aread(env)
    val env = env.println("byte1 = " + byte1)
    val (byte2, env) = aread(env)
    val env = env.println("byte2 = " + byte2)
  }
}

我相信这将被翻译成逻辑上的等价物:

def read(callback: Tuple2[Byte,ENV] => ENV, env: ENV): ENV =
  env.myCallback(callback)
def pure(val env: ENV): ENV {
  read(callback,env)
  def callback(x: Tuple2[Byte,ENV]): ENV {
    val (byte1, env) = x
    val env = env.println("byte1 = " + byte1)
    read(callback2,env)
    def callback2(x: Tuple2[Byte,ENV]): ENV {
      val (byte2, env) = x
      val env = env.println("byte2 = " + byte2)
    }
  }
}

由于显式环境,这变得越来越嘈杂。

顺便指出,Scala 没有 Haskell 的全局类型推断,因此据我所知无法支持隐式提升到状态 monad 的 unit (作为隐藏显式环境的一种可能策略),因为 Haskell 的全局 (Hindley-Milner) 类型推断取决于不支持钻石多重虚拟继承

Given the canonical example from the research paper for Scala's delimited continuations, modified slightly so the function input to shift is given the name f and thus is no longer anonymous.

def f(k: Int => Int): Int = k(k(k(7)))
reset(
  shift(f) + 1   // replace from here down with `f(k)` and move to `k`
) * 2

The Scala plugin transforms this example such that the computation (within the input argument of reset) starting from each shift to the invocation of reset is replaced with the function (e.g. f) input to shift.

The replaced computation is shifted (i.e. moved) into a function k. The function f inputs the function k, where k contains the replaced computation, k inputs x: Int, and the computation in k replaces shift(f) with x.

f(k) * 2
def k(x: Int): Int = x + 1

Which has the same effect as:

k(k(k(7))) * 2
def k(x: Int): Int = x + 1

Note the type Int of the input parameter x (i.e. the type signature of k) was given by the type signature of the input parameter of f.

Another borrowed example with the conceptually equivalent abstraction, i.e. read is the function input to shift:

def read(callback: Byte => Unit): Unit = myCallback = callback
reset {
  val byte = "byte"

  val byte1 = shift(read)   // replace from here with `read(callback)` and move to `callback`
  println(byte + "1 = " + byte1)
  val byte2 = shift(read)   // replace from here with `read(callback)` and move to `callback`
  println(byte + "2 = " + byte2)
}

I believe this would be translated to the logical equivalent of:

val byte = "byte"

read(callback)
def callback(x: Byte): Unit {
  val byte1 = x
  println(byte + "1 = " + byte1)
  read(callback2)
  def callback2(x: Byte): Unit {
    val byte2 = x
    println(byte + "2 = " + byte1)
  }
}

I hope this elucidates the coherent common abstraction which was somewhat obfuscated by prior presentation of these two examples. For example, the canonical first example was presented in the research paper as an anonymous function, instead of my named f, thus it was not immediately clear to some readers that it was abstractly analogous to the read in the borrowed second example.

Thus delimited continuations create the illusion of an inversion-of-control from "you call me from outside of reset" to "I call you inside reset".

Note the return type of f is, but k is not, required to be the same as the return type of reset, i.e. f has the freedom to declare any return type for k as long as f returns the same type as reset. Ditto for read and capture (see also ENV below).


Delimited continuations do not implicitly invert the control of state, e.g. read and callback are not pure functions. Thus the caller can not create referentially transparent expressions and thus does not have declarative (a.k.a. transparent) control over intended imperative semantics.

We can explicitly achieve pure functions with delimited continuations.

def aread(env: ENV): Tuple2[Byte,ENV] {
  def read(callback: Tuple2[Byte,ENV] => ENV): ENV = env.myCallback(callback)
  shift(read)
}
def pure(val env: ENV): ENV {
  reset {
    val (byte1, env) = aread(env)
    val env = env.println("byte1 = " + byte1)
    val (byte2, env) = aread(env)
    val env = env.println("byte2 = " + byte2)
  }
}

I believe this would be translated to the logical equivalent of:

def read(callback: Tuple2[Byte,ENV] => ENV, env: ENV): ENV =
  env.myCallback(callback)
def pure(val env: ENV): ENV {
  read(callback,env)
  def callback(x: Tuple2[Byte,ENV]): ENV {
    val (byte1, env) = x
    val env = env.println("byte1 = " + byte1)
    read(callback2,env)
    def callback2(x: Tuple2[Byte,ENV]): ENV {
      val (byte2, env) = x
      val env = env.println("byte2 = " + byte2)
    }
  }
}

This is getting noisy, because of the explicit environment.

Tangentially note, Scala does not have Haskell's global type inference and thus as far as I know couldn't support implicit lifting to a state monad's unit (as one possible strategy for hiding the explicit environment), because Haskell's global (Hindley-Milner) type inference depends on not supporting diamond multiple virtual inheritance.

花海 2024-08-13 10:46:56

延续捕获计算的状态,以便稍后调用。

将移位表达式和重置表达式保留为函数之间的计算。在移位表达式中,这个函数称为 k,它是延续。您可以传递它,稍后调用它,甚至不止一次。

我认为重置表达式返回的值是 => 之后的移位表达式内的表达式的值,但对此我不太确定。

因此,通过延续,您可以将一段相当任意且非本地的代码包装在函数中。这可用于实现非标准控制流,例如协程或回溯。

因此应该在系统级别使用延续。将它们散布在应用程序代码中肯定会带来噩梦,比使用 goto 的最糟糕的意大利面条代码更糟糕。

免责声明:我对Scala中的延续没有深入的了解,我只是通过查看示例并了解Scheme的延续来推断。

Continuation capture the state of a computation, to be invoked later.

Think of the computation between leaving the shift expression and leaving the reset expression as a function. Inside the shift expression this function is called k, it is the continuation. You can pass it around, invoke it later, even more than once.

I think the value returned by the reset expression is the value of the expression inside the shift expression after the =>, but about this I'm not quite sure.

So with continuations you can wrap up a rather arbitrary and non-local piece of code in a function. This can be used to implement non-standard control flow, such as coroutining or backtracking.

So continuations should be used on a system level. Sprinkling them through your application code would be a sure recipe for nightmares, much worse than the worst spaghetti code using goto could ever be.

Disclaimer: I have no in depth understanding of continuations in Scala, I just inferred it from looking at the examples and knowing continuations from Scheme.

飞烟轻若梦 2024-08-13 10:46:56

从我的角度来看,这里给出了最好的解释: http:// jim-mcbeath.blogspot.ru/2010/08/delimited-continuations.html

示例之一:

为了更清楚地看到控制流程,你可以执行这个
代码片段:

reset {
    println("A")
    shift { k1: (Unit=>Unit) =>
        println("B")
        k1()
        println("C")
    }
    println("D")
    shift { k2: (Unit=>Unit) =>
        println("E")
        k2()
        println("F")
    }
    println("G")
}

这是上面代码产生的输出:

A
B
D
E
G
F
C

From my point of view, the best explanation was given here: http://jim-mcbeath.blogspot.ru/2010/08/delimited-continuations.html

One of examples:

To see the control flow a little more clearly, you can execute this
code snippet:

reset {
    println("A")
    shift { k1: (Unit=>Unit) =>
        println("B")
        k1()
        println("C")
    }
    println("D")
    shift { k2: (Unit=>Unit) =>
        println("E")
        k2()
        println("F")
    }
    println("G")
}

Here's the output the above code produces:

A
B
D
E
G
F
C
墨落成白 2024-08-13 10:46:56

另一篇关于 Scala 延续的文章(最近的 - 2016 年 5 月)是:
"时间旅行in Scala:Scala 中的 CPS(scala 的延续)
Shivansh Srivastava (shiv4nsh)
它还引用了 Jim McBeathDmitry Bespalov< 中提到的文章 /a> 的答案

但在此之前,它是这样描述Continuations的:

延续是计算机程序控制状态的抽象表示
所以它实际上意味着它是一种数据结构,表示流程执行中给定点的计算过程;创建的数据结构可以被编程语言访问,而不是隐藏在运行时环境中。

为了进一步解释它,我们可以举一个最经典的例子,

假设您在厨房的冰箱前,正在考虑吃三明治。您就在那里继续并把它放在口袋里。
然后你从冰箱里拿出一些火鸡和面包,给自己做一个三明治,现在它就放在柜台上。
您调用口袋中的延续,然后您发现自己再次站在冰箱前,想着三明治。但幸运的是,柜台上有一个三明治,而且制作它的所有材料都没有了。所以你吃它。 :-)

在此描述中,sandwich程序数据的一部分(例如,堆上的对象),而不是调用“make sandwich””例程然后返回,该人调用了“用当前继续制作三明治”例程,该例程创建三明治,然后从执行停止的地方继续。

话虽这么说,正如 2014 年 4 月,Scala 2.11.0-RC1

我们正在寻找维护者来接管以下模块:scala-swing,< a href="https://github.com/scala/scala-continuations" rel="nofollow noreferrer">scala-continuations。
如果没有找到新的维护者,2.12 将不会包含它们
我们可能会继续维护其他模块(scala-xml、scala-parser-combinators),但仍然非常感谢您的帮助。

Another (more recent -- May 2016) article on Scala continuations is:
"Time Travel in Scala: CPS in Scala (scala’s continuation)" by
Shivansh Srivastava (shiv4nsh).
It also refers to Jim McBeath's article mentioned in Dmitry Bespalov's answer.

But before that, it describes Continuations like so:

A continuation is an abstract representation of the control state of a computer program.
So what it actually means is that it is a data structure that represents the computational process at a given point in the process’s execution; the created data structure can be accessed by the programming language, instead of being hidden in the runtime environment.

To explain it further we can have one of the most classic example,

Say you’re in the kitchen in front of the refrigerator, thinking about a sandwich. You take a continuation right there and stick it in your pocket.
Then you get some turkey and bread out of the refrigerator and make yourself a sandwich, which is now sitting on the counter.
You invoke the continuation in your pocket, and you find yourself standing in front of the refrigerator again, thinking about a sandwich. But fortunately, there’s a sandwich on the counter, and all the materials used to make it are gone. So you eat it. :-)

In this description, the sandwich is part of the program data (e.g., an object on the heap), and rather than calling a “make sandwich” routine and then returning, the person called a “make sandwich with current continuation” routine, which creates the sandwich and then continues where execution left off.

That being said, as announced in April 2014 for Scala 2.11.0-RC1

We are looking for maintainers to take over the following modules: scala-swing, scala-continuations.
2.12 will not include them if no new maintainer is found.
We will likely keep maintaining the other modules (scala-xml, scala-parser-combinators), but help is still greatly appreciated.

送君千里 2024-08-13 10:46:56

通过有意义的示例实现 Scala Continuations

让我们定义 from0to10 来表达从 0 到 10 的迭代思想:

def from0to10() = shift { (cont: Int => Unit) =>
   for ( i <- 0 to 10 ) {
     cont(i)
   }
}

现在,

reset {
  val x = from0to10()
  print(s"$x ")
}
println()

输出:

0 1 2 3 4 5 6 7 8 9 10 

事实上,我们不需要 x< /code>:

reset {
  print(s"${from0to10()} ")
}
println()

打印相同的结果。

reset {
  print(s"(${from0to10()},${from0to10()}) ")
}
println()

打印所有对:

(0,0) (0,1) (0,2) (0,3) (0,4) (0,5) (0,6) (0,7) (0,8) (0,9) (0,10) (1,0) (1,1) (1,2) (1,3) (1,4) (1,5) (1,6) (1,7) (1,8) (1,9) (1,10) (2,0) (2,1) (2,2) (2,3) (2,4) (2,5) (2,6) (2,7) (2,8) (2,9) (2,10) (3,0) (3,1) (3,2) (3,3) (3,4) (3,5) (3,6) (3,7) (3,8) (3,9) (3,10) (4,0) (4,1) (4,2) (4,3) (4,4) (4,5) (4,6) (4,7) (4,8) (4,9) (4,10) (5,0) (5,1) (5,2) (5,3) (5,4) (5,5) (5,6) (5,7) (5,8) (5,9) (5,10) (6,0) (6,1) (6,2) (6,3) (6,4) (6,5) (6,6) (6,7) (6,8) (6,9) (6,10) (7,0) (7,1) (7,2) (7,3) (7,4) (7,5) (7,6) (7,7) (7,8) (7,9) (7,10) (8,0) (8,1) (8,2) (8,3) (8,4) (8,5) (8,6) (8,7) (8,8) (8,9) (8,10) (9,0) (9,1) (9,2) (9,3) (9,4) (9,5) (9,6) (9,7) (9,8) (9,9) (9,10) (10,0) (10,1) (10,2) (10,3) (10,4) (10,5) (10,6) (10,7) (10,8) (10,9) (10,10) 

现在,这是如何工作的?

被调用代码from0to10调用代码。在本例中,它是 reset 之后的块。传递给被调用代码的参数之一是返回地址,它显示调用代码的哪一部分尚未执行 (**)。调用代码的该部分是延续。被调用的代码可以对该参数执行任何它决定的操作:将控制权传递给它,或忽略,或多次调用它。这里 from0to10 为 0..10 范围内的每个整数调用该延续。

def from0to10() = shift { (cont: Int => Unit) =>
   for ( i <- 0 to 10 ) {
     cont(i) // call the continuation
   }
}

但延续到哪里结束呢?这很重要,因为延续中的最后一个返回将控制权返回给被调用的代码from0to10。在 Scala 中,它在 reset 块结束处结束 (*)。

现在,我们看到延续被声明为 cont: Int =>;单位。为什么?我们将 from0to10 调用为 val x = from0to10(),而 Int 是转到 x 的值类型。 Unit表示reset后的块必须不返回任何值(否则会出现类型错误)。一般来说,有 4 种类型签名:函数输入、延续输入、延续结果、函数结果。所有四个都必须与调用上下文匹配。

上面,我们打印了值对。让我们打印乘法口诀表。但是我们如何在每一行之后输出 \n 呢?

函数 back 让我们指定当控制返回时必须执行的操作,从延续到调用它的代码。

def back(action: => Unit) = shift { (cont: Unit => Unit) =>
  cont()
  action
}

back 首先调用其延续,然后执行操作

reset {
  val i = from0to10()
  back { println() }
  val j = from0to10
  print(f"${i*j}%4d ") // printf-like formatted i*j
}

它打印出:

   0    0    0    0    0    0    0    0    0    0    0 
   0    1    2    3    4    5    6    7    8    9   10 
   0    2    4    6    8   10   12   14   16   18   20 
   0    3    6    9   12   15   18   21   24   27   30 
   0    4    8   12   16   20   24   28   32   36   40 
   0    5   10   15   20   25   30   35   40   45   50 
   0    6   12   18   24   30   36   42   48   54   60 
   0    7   14   21   28   35   42   49   56   63   70 
   0    8   16   24   32   40   48   56   64   72   80 
   0    9   18   27   36   45   54   63   72   81   90 
   0   10   20   30   40   50   60   70   80   90  100 

好吧,现在是时候做一些脑筋急转弯了。有两次 from0to10 调用。第一个 from0to10 的延续是什么?它遵循二进制代码中 from0to10 的调用,但在源代码中它还包含赋值语句 val i =。它在 reset 块结束处结束,但 reset 块的末尾不会将控制返回给第一个 from0to10reset 块的末尾将控制权返回给第二个 from0to10,后者最终将控制权返回给 back,它是 back 将控制权返回给第一次调用 from0to10。当第一个(是的!第一个!)from0to10 退出时,整个 reset 块就会退出。

这种返回控制权的方法称为回溯,这是一种非常古老的技术,至少从 Prolog 和面向人工智能的 Lisp 衍生产品时代就为人所知。

resetshift 这两个名称用词不当。这些名称最好留给按位运算。 reset 定义延续边界,而 shift 从调用堆栈中获取延续。

注意 (

*) 在 Scala 中,延续在 reset 块结束的地方结束。另一种可能的方法是让它在函数结束的地方结束。

(**) 被调用代码的参数之一是返回地址,它显示调用代码的哪一部分尚未执行。在 Scala 中,返回地址序列用于那。多少?自进入 reset 块以来放置在调用堆栈上的所有返回地址。


UPD 第 2 部分
丢弃延续:过滤

def onEven(x:Int) = shift { (cont: Unit => Unit) =>
  if ((x&1)==0) {
    cont() // call continuation only for even numbers
  }
}
reset {
  back { println() }
  val x = from0to10()
  onEven(x)
  print(s"$x ")
}

这将打印:

0 2 4 6 8 10 

让我们分解两个重要的操作:丢弃延续 (fail()) 并将控制权传递给它 (succ()):

// fail: just discard the continuation, force control to return back
def fail() = shift { (cont: Unit => Unit) => }
// succ: does nothing (well, passes control to the continuation), but has a funny signature
def succ():Unit @cpsParam[Unit,Unit] = { }
// def succ() = shift { (cont: Unit => Unit) => cont() }

两个版本的 succ() (上面)都可以工作。事实证明,shift 有一个有趣的签名,尽管 succ() 不执行任何操作,但它必须具有该签名以实现类型平衡。

reset {
  back { println() }
  val x = from0to10()
  if ((x&1)==0) {
    succ()
  } else {
    fail()
  }
  print(s"$x ")
}

正如预期的那样,它打印出

0 2 4 6 8 10

Within a function, succ() is not required:

def onTrue(b:Boolean) = {
  if(!b) {
    fail()
  }
}
reset {
  back { println() }
  val x = from0to10()
  onTrue ((x&1)==0)
  print(s"$x ")
}

再次,它打印出来

0 2 4 6 8 10

现在,让我们通过 onEven()< 定义 onOdd() /code>:

// negation: the hard way
class ControlTransferException extends Exception {}
def onOdd(x:Int) = shift { (cont: Unit => Unit) =>
  try {
    reset {
      onEven(x)
      throw new ControlTransferException() // return is not allowed here
    }
    cont()
  } catch {
    case e: ControlTransferException =>
    case t: Throwable => throw t
  }
}
reset {
  back { println() }
  val x = from0to10()
  onOdd(x)
  print(s"$x ")
}

上面,如果x是偶数,则抛出异常并且不调用延续;如果 x 为奇数,则不会引发异常并调用延续。
上面的代码打印:

1 3 5 7 9 

Scala Continuations via Meaningful Examples

Let us define from0to10 that expresses the idea of iteration from 0 to 10:

def from0to10() = shift { (cont: Int => Unit) =>
   for ( i <- 0 to 10 ) {
     cont(i)
   }
}

Now,

reset {
  val x = from0to10()
  print(s"$x ")
}
println()

prints:

0 1 2 3 4 5 6 7 8 9 10 

In fact, we do not need x:

reset {
  print(s"${from0to10()} ")
}
println()

prints the same result.

And

reset {
  print(s"(${from0to10()},${from0to10()}) ")
}
println()

prints all pairs:

(0,0) (0,1) (0,2) (0,3) (0,4) (0,5) (0,6) (0,7) (0,8) (0,9) (0,10) (1,0) (1,1) (1,2) (1,3) (1,4) (1,5) (1,6) (1,7) (1,8) (1,9) (1,10) (2,0) (2,1) (2,2) (2,3) (2,4) (2,5) (2,6) (2,7) (2,8) (2,9) (2,10) (3,0) (3,1) (3,2) (3,3) (3,4) (3,5) (3,6) (3,7) (3,8) (3,9) (3,10) (4,0) (4,1) (4,2) (4,3) (4,4) (4,5) (4,6) (4,7) (4,8) (4,9) (4,10) (5,0) (5,1) (5,2) (5,3) (5,4) (5,5) (5,6) (5,7) (5,8) (5,9) (5,10) (6,0) (6,1) (6,2) (6,3) (6,4) (6,5) (6,6) (6,7) (6,8) (6,9) (6,10) (7,0) (7,1) (7,2) (7,3) (7,4) (7,5) (7,6) (7,7) (7,8) (7,9) (7,10) (8,0) (8,1) (8,2) (8,3) (8,4) (8,5) (8,6) (8,7) (8,8) (8,9) (8,10) (9,0) (9,1) (9,2) (9,3) (9,4) (9,5) (9,6) (9,7) (9,8) (9,9) (9,10) (10,0) (10,1) (10,2) (10,3) (10,4) (10,5) (10,6) (10,7) (10,8) (10,9) (10,10) 

Now, how does that work?

There is the called code, from0to10, and the calling code. In this case, it is the block that follows reset. One of the parameters passed to the called code is a return address that shows what part of the calling code has not yet been executed (**). That part of the calling code is the continuation. The called code can do with that parameter whatever it decides to: pass control to it, or ignore, or call it multiple times. Here from0to10 calls that continuation for each integer in the range 0..10.

def from0to10() = shift { (cont: Int => Unit) =>
   for ( i <- 0 to 10 ) {
     cont(i) // call the continuation
   }
}

But where does the continuation end? This is important because the last return from the continuation returns control to the called code, from0to10. In Scala, it ends where the reset block ends (*).

Now, we see that the continuation is declared as cont: Int => Unit. Why? We invoke from0to10 as val x = from0to10(), and Int is the type of value that goes to x. Unit means that the block after reset must return no value (otherwise there will be a type error). In general, there are 4 type signatures: function input, continuation input, continuation result, function result. All four must match the invocation context.

Above, we printed pairs of values. Let us print the multiplication table. But how do we output \n after each row?

The function back lets us specify what must be done when control returns back, from the continuation to the code that called it.

def back(action: => Unit) = shift { (cont: Unit => Unit) =>
  cont()
  action
}

back first calls its continuation, and then performs the action.

reset {
  val i = from0to10()
  back { println() }
  val j = from0to10
  print(f"${i*j}%4d ") // printf-like formatted i*j
}

It prints:

   0    0    0    0    0    0    0    0    0    0    0 
   0    1    2    3    4    5    6    7    8    9   10 
   0    2    4    6    8   10   12   14   16   18   20 
   0    3    6    9   12   15   18   21   24   27   30 
   0    4    8   12   16   20   24   28   32   36   40 
   0    5   10   15   20   25   30   35   40   45   50 
   0    6   12   18   24   30   36   42   48   54   60 
   0    7   14   21   28   35   42   49   56   63   70 
   0    8   16   24   32   40   48   56   64   72   80 
   0    9   18   27   36   45   54   63   72   81   90 
   0   10   20   30   40   50   60   70   80   90  100 

Well, now it's time for some brain-twisters. There are two invocations of from0to10. What is the continuation for the first from0to10? It follows the invocation of from0to10 in the binary code, but in the source code it also includes the assignment statement val i =. It ends where the reset block ends, but the end of the reset block does not return control to the first from0to10. The end of the reset block returns control to the 2nd from0to10, that in turn eventually returns control to back, and it is back that returns control to the first invocation of from0to10. When the first (yes! 1st!) from0to10 exits, the whole reset block is exited.

Such method of returning control back is called backtracking, it is a very old technique, known at least from the times of Prolog and AI-oriented Lisp derivatives.

The names reset and shift are misnomers. These names should better have been left for the bitwise operations. reset defines continuation boundaries, and shift takes a continuation from the call stack.

Note(s)

(*) In Scala, the continuation ends where the reset block ends. Another possible approach would be to let it end where the function ends.

(**) One of the parameters of the called code is a return address that shows what part of the calling code has not yet been executed. Well, in Scala, a sequence of return addresses is used for that. How many? All of the return addresses placed on the call stack since entering the reset block.


UPD Part 2
Discarding Continuations: Filtering

def onEven(x:Int) = shift { (cont: Unit => Unit) =>
  if ((x&1)==0) {
    cont() // call continuation only for even numbers
  }
}
reset {
  back { println() }
  val x = from0to10()
  onEven(x)
  print(s"$x ")
}

This prints:

0 2 4 6 8 10 

Let us factor out two important operations: discarding the continuation (fail()) and passing control on to it (succ()):

// fail: just discard the continuation, force control to return back
def fail() = shift { (cont: Unit => Unit) => }
// succ: does nothing (well, passes control to the continuation), but has a funny signature
def succ():Unit @cpsParam[Unit,Unit] = { }
// def succ() = shift { (cont: Unit => Unit) => cont() }

Both versions of succ() (above) work. It turns out that shift has a funny signature, and although succ() does nothing, it must have that signature for type balance.

reset {
  back { println() }
  val x = from0to10()
  if ((x&1)==0) {
    succ()
  } else {
    fail()
  }
  print(s"$x ")
}

as expected, it prints

0 2 4 6 8 10

Within a function, succ() is not necessary:

def onTrue(b:Boolean) = {
  if(!b) {
    fail()
  }
}
reset {
  back { println() }
  val x = from0to10()
  onTrue ((x&1)==0)
  print(s"$x ")
}

again, it prints

0 2 4 6 8 10

Now, let us define onOdd() via onEven():

// negation: the hard way
class ControlTransferException extends Exception {}
def onOdd(x:Int) = shift { (cont: Unit => Unit) =>
  try {
    reset {
      onEven(x)
      throw new ControlTransferException() // return is not allowed here
    }
    cont()
  } catch {
    case e: ControlTransferException =>
    case t: Throwable => throw t
  }
}
reset {
  back { println() }
  val x = from0to10()
  onOdd(x)
  print(s"$x ")
}

Above, if x is even, an exception is thrown and the continuation is not called; if x is odd, the exception is not thrown and the continuation is called.
The above code prints:

1 3 5 7 9 
~没有更多了~
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