scala HList 只是一种复杂的元组编写方式吗？

Are HLists nothing more than a convoluted way of writing tuples?

提问by Malte Schwerhoff

I am really interested in finding out where the differences are, and more generally, to identify canonical use cases where HLists cannot be used (or rather, don't yield any benefits over regular lists).

我真的很想找出差异在哪里，更一般地说，以确定不能使用 HLists 的规范用例（或者更确切地说，不产生任何优于常规列表的好处）。

(I am aware that there are 22 (I believe) TupleNin Scala, whereas one only needs a single HList, but that is not the kind of conceptual difference I am interested in.)

（我知道TupleNScala中有 22 个（我相信），而一个只需要一个 HList，但这不是我感兴趣的那种概念差异。）

I've marked a couple of questions in the text below. It might not actually be necessary to answer them, they are more meant to point out things that are unclear to me, and to guide the discussion in certain directions.

我在下面的文本中标记了几个问题。实际上可能没有必要回答它们，它们更多的是指出我不清楚的事情，并在某些方向上引导讨论。

Motivation

动机

I've recently seen a couple of answers on SO where people suggested to use HLists (for example, as provided by Shapeless), including a deleted answer to this question. It gave rise to this discussion, which in turn sparked this question.

我最近在 SO 上看到了几个答案，人们建议使用 HLists（例如，由Shapeless提供），包括对此问题的已删除答案。它引起了这个讨论，这反过来又引发了这个问题。

Intro

介绍

It seems to me, that hlists are only useful when you know the number of elements and their precise types statically. The number is actually not crucial, but it seems unlikely that you ever need to generate a list with elements of varying but statically precisely known types, but that you don't statically know their number. Question 1:Could you even write such an example, e.g., in a loop? My intuition is that having a statically precise hlist with a statically unknown number of arbitrary elements (arbitrary relative to a given class hierarchy) just isn't compatible.

在我看来，只有当您静态地知道元素的数量及其精确类型时，hlist 才有用。数字实际上并不重要，但您似乎不太可能需要生成一个包含可变但静态精确已知类型的元素的列表，但您并不静态地知道它们的数量。问题 1：你能写一个这样的例子吗，例如，在一个循环中？我的直觉是，拥有一个静态精确的 hlist 和静态未知数量的任意元素（相对于给定的类层次结构是任意的）只是不兼容。

HLists vs. Tuples

HLists 与元组

If this is true, i.e, you statically know number and type - Question 2:why not just use an n-tuple? Sure, you can typesafely map and fold over an HList (which you can also, but nottypesafely, do over a tuple with the help of productIterator), but since number and type of the elements are statically known you could probably just access the tuple elements directly and perform the operations.

如果这是真的，即您静态地知道数字和类型 -问题 2：为什么不只使用 n 元组？当然，您可以类型安全地映射和折叠 HList（您也可以，但不是类型安全地，在 的帮助下对元组进行处理productIterator），但是由于元素的数量和类型是静态已知的，因此您可能只需访问元组元素直接执行操作。

On the other hand, if the function fyou map over an hlist is so generic that it accepts all elements - Question 3:why not use it via productIterator.map? Ok, one interesting difference could come from method overloading: if we had several overloaded f's, having the stronger type information provided by the hlist (in contrast to the productIterator) could allow the compiler to choose a more specific f. However, I am not sure if that would actually work in Scala, since methods and functions are not the same.

另一方面，如果f您映射到 hlist的函数是如此通用以至于它接受所有元素 -问题 3：为什么不使用它 via productIterator.map？好吧，一个有趣的区别可能来自方法重载：如果我们有几个重载f的 ，拥有由 hlist 提供的更强的类型信息（与 productIterator 相反）可以允许编译器选择一个更具体的f. 但是，我不确定这是否真的适用于 Scala，因为方法和函数不一样。

HLists and user input

HLists 和用户输入

Building on the same assumption, namely, that you need to know number and types of the elements statically - Question 4:can hlists be used in situations where the elements depend on any kind of user interaction? E.g., imagine populating an hlist with elements inside a loop; the elements are read from somewhere (UI, config file, actor interaction, network) until a certain condition holds. What would the type of the hlist be? Similar for an interface specification getElements: HList[...] that should work with lists of statically unknown length, and that allows component A in a system to get such a list of arbitrary elements from component B.

基于相同的假设，即您需要静态地知道元素的数量和类型 -问题 4：可以在元素依赖于任何类型的用户交互的情况下使用 hlists 吗？例如，想象用循环内的元素填充 hlist；从某处（UI、配置文件、actor 交互、网络）读取元素，直到某个条件成立。hlist 的类型是什么？与接口规范 getElements: HList[...] 类似，它应该与静态未知长度的列表一起工作，并且允许系统中的组件 A 从组件 B 获取这样的任意元素列表。

采纳答案by Miles Sabin

Addressing questions one to three: one of the main applications for HListsis abstracting over arity. Arity is typically statically known at any given use site of an abstraction, but varies from site to site. Take this, from shapeless's examples,

解决一到三个问题： 的主要应用之一HLists是对元数进行抽象。Arity 通常在抽象的任何给定使用站点是静态已知的，但因站点而异。拿这个，从 shapeless 的例子中，

def flatten[T <: Product, L <: HList](t : T)
  (implicit hl : HListerAux[T, L], flatten : Flatten[L]) : flatten.Out =
    flatten(hl(t))

val t1 = (1, ((2, 3), 4))
val f1 = flatten(t1)     // Inferred type is Int :: Int :: Int :: Int :: HNil
val l1 = f1.toList       // Inferred type is List[Int]

val t2 = (23, ((true, 2.0, "foo"), "bar"), (13, false))
val f2 = flatten(t2)
val t2b = f2.tupled
// Inferred type of t2b is (Int, Boolean, Double, String, String, Int, Boolean)

Without using HLists(or something equivalent) to abstract over the arity of the tuple arguments to flattenit would be impossible to have a single implementation which could accept arguments of these two very different shapes and transform them in a type safe way.

如果不使用HLists（或类似的东西）抽象元组参数的数量，flatten就不可能有一个单一的实现来接受这两种截然不同的形状的参数并以类型安全的方式转换它们。

The ability to abstract over arity is likely to be of interest anywhere that fixed arities are involved: as well as tuples, as above, that includes method/function parameter lists, and case classes. See herefor examples of how we might abstract over the arity of arbitrary case classes to obtain type class instances almost automatically,

在涉及固定元数的任何地方，对元数进行抽象的能力可能会引起人们的兴趣：以及元组，如上所述，包括方法/函数参数列表和案例类。有关我们如何抽象任意 case 类的数量以几乎自动获取类型类实例的示例，请参见此处，

// A pair of arbitrary case classes
case class Foo(i : Int, s : String)
case class Bar(b : Boolean, s : String, d : Double)

// Publish their `HListIso`'s
implicit def fooIso = Iso.hlist(Foo.apply _, Foo.unapply _)
implicit def barIso = Iso.hlist(Bar.apply _, Bar.unapply _)

// And now they're monoids ...

implicitly[Monoid[Foo]]
val f = Foo(13, "foo") |+| Foo(23, "bar")
assert(f == Foo(36, "foobar"))

implicitly[Monoid[Bar]]
val b = Bar(true, "foo", 1.0) |+| Bar(false, "bar", 3.0)
assert(b == Bar(true, "foobar", 4.0))

There's no runtime iterationhere, but there is duplication, which the use of HLists(or equivalent structures) can eliminate. Of course, if your tolerance for repetitive boilerplate is high, you can get the same result by writing multiple implementations for each and every shape that you care about.

这里没有运行时迭代，但有重复，使用HLists（或等效结构）可以消除重复。当然，如果您对重复样板的容忍度很高，您可以通过为您关心的每个形状编写多个实现来获得相同的结果。

In question three you ask "... if the function f you map over an hlist is so generic that it accepts all elements ... why not use it via productIterator.map?". If the function you map over an HList really is of the form Any => Tthen mapping over productIteratorwill serve you perfectly well. But functions of the form Any => Taren't typically that interesting (at least, they aren't unless they type cast internally). shapeless provides a form of polymorphic function value which allows the compiler to select type-specific cases in exactly the way you're doubtful about. For instance,

在问题三中，您会问“...如果您映射到 hlist 的函数是如此通用以至于它接受所有元素...为什么不通过 productIterator.map 使用它？”。如果您映射到 HList 的函数确实是这种形式，Any => T那么映射productIterator将非常适合您。但是表单的函数Any => T通常没有那么有趣（至少，除非它们在内部进行类型转换，否则它们不是）。shapeless 提供了一种多态函数值的形式，它允许编译器以您所怀疑的方式选择特定于类型的情况。例如，

// size is a function from values of arbitrary type to a 'size' which is
// defined via type specific cases
object size extends Poly1 {
  implicit def default[T] = at[T](t => 1)
  implicit def caseString = at[String](_.length)
  implicit def caseList[T] = at[List[T]](_.length)
}

scala> val l = 23 :: "foo" :: List('a', 'b') :: true :: HNil
l: Int :: String :: List[Char] :: Boolean :: HNil =
  23 :: foo :: List(a, b) :: true :: HNil

scala> (l map size).toList
res1: List[Int] = List(1, 3, 2, 1)

With respect to your question four, about user input, there are two cases to consider. The first is situations where we can dynamically establish a context which guarantees that a known static condition obtains. In these kinds of scenarios it's perfectly possible to apply shapeless techniques, but clearly with the proviso that if the static condition doesn'tobtain at runtime then we have to follow an alternative path. Unsurprisingly, this means that methods which are sensitive to dynamic conditions have to yield optional results. Here's an example using HLists,

关于你的问题四，关于用户输入，有两种情况需要考虑。第一种情况是我们可以动态建立上下文以保证获得已知的静态条件。在这些场景中，完全有可能应用无形技术，但很明显，如果在运行时无法获得静态条件，那么我们必须遵循替代路径。不出所料，这意味着对动态条件敏感的方法必须产生可选的结果。这是一个使用HLists的例子，

trait Fruit
case class Apple() extends Fruit
case class Pear() extends Fruit

type FFFF = Fruit :: Fruit :: Fruit :: Fruit :: HNil
type APAP = Apple :: Pear :: Apple :: Pear :: HNil

val a : Apple = Apple()
val p : Pear = Pear()

val l = List(a, p, a, p) // Inferred type is List[Fruit]

The type of ldoesn't capture the length of the list, or the precise types of its elements. However, if we expect it to have a specific form (ie. if it ought to conform to some known, fixed schema), then we can attempt to establish that fact and act accordingly,

的类型l不捕获列表的长度或其元素的精确类型。但是，如果我们期望它具有特定的形式（即，如果它应该符合某些已知的固定模式），那么我们可以尝试建立该事实并采取相应的行动，

scala> import Traversables._
import Traversables._

scala> val apap = l.toHList[Apple :: Pear :: Apple :: Pear :: HNil]
res0: Option[Apple :: Pear :: Apple :: Pear :: HNil] =
  Some(Apple() :: Pear() :: Apple() :: Pear() :: HNil)

scala> apap.map(_.tail.head)
res1: Option[Pear] = Some(Pear())

There are other situations where we might not care about the actual length of a given list, other than that it is the same length as some other list. Again, this is something that shapeless supports, both fully statically, and also in a mixed static/dynamic context as above. See herefor an extended example.

在其他情况下，我们可能不关心给定列表的实际长度，除了它与其他列表的长度相同。同样，这也是无形支持的东西，无论是完全静态的，还是在上面的混合静态/动态环境中。有关扩展示例，请参见此处。

It is true, as you observe, that all of these mechanism require static type information to be available, at least conditionally, and that would seem to exclude these techniques from being usable in a completely dynamic environment, fully driven by externally provided untyped data. But with the advent of the support for runtime compilation as a component of Scala reflection in 2.10, even this is no longer an insuperable obstacle ... we can use runtime compilation to provide a form of lightweight stagingand have our static typing performed at runtime in response to dynamic data: excerpt from the preceding below ... follow the link for the full example,

正如您所观察到的，所有这些机制确实需要静态类型信息可用，至少有条件地可用，这似乎排除了这些技术在完全由外部提供的无类型数据驱动的完全动态环境中可用。但是随着 2.10 中对运行时编译作为 Scala 反射组件的支持的出现，即使这也不再是不可逾越的障碍……我们可以使用运行时编译来提供一种轻量级登台形式，并在运行时执行我们的静态类型响应动态数据：摘自以下内容...请点击完整示例的链接，

val t1 : (Any, Any) = (23, "foo") // Specific element types erased
val t2 : (Any, Any) = (true, 2.0) // Specific element types erased

// Type class instances selected on static type at runtime!
val c1 = stagedConsumeTuple(t1) // Uses intString instance
assert(c1 == "23foo")

val c2 = stagedConsumeTuple(t2) // Uses booleanDouble instance
assert(c2 == "+2.0")

I'm sure @PLT_Boratwill have something to say about that, given his sage comments about dependently typed programming languages;-)

考虑到他对依赖类型编程语言的睿智评论，我相信@PLT_Borat会对此有话要说；-)

回答by Dan Burton

Just to be clear, an HList is essentially nothing more than a stack of Tuple2with slightly different sugar on top.

需要明确的是，HList 本质上只不过是一堆Tuple2顶部略有不同的糖。

def hcons[A,B](head : A, tail : B) = (a,b)
def hnil = Unit

hcons("foo", hcons(3, hnil)) : (String, (Int, Unit))

So your question is essentially about the differences between using nested tuples vs flat tuples, but the two are isomorphic so in the end there really is no difference except convenience in which library functions can be used and which notation can be used.

所以你的问题本质上是关于使用嵌套元组和平面元组之间的区别，但两者是同构的，所以最后真的没有区别，除了可以使用库函数和可以使用哪种符号的便利性。

回答by Kim Stebel

There are a lot of things you can't do (well) with tuples:

有很多事情你不能用元组做（很好）：

• write a generic prepend/append function
• write a reverse function
• write a concat function
• ...

• 编写一个通用的前置/追加函数
• 写一个反向函数
• 写一个 concat 函数
• ...

You can do all of that with tuples of course, but not in the general case. So using HLists makes your code more DRY.

当然，您可以使用元组完成所有这些操作，但在一般情况下则不然。因此，使用 HLists 会使您的代码更加 DRY。

回答by clay

I can explain this in super simple language:

我可以用超级简单的语言解释这一点：

The tuple vs list naming isn't significant. HLists could be named as HTuples. The difference is that in Scala+Haskell, you can do this with a tuple (using Scala syntax):

元组与列表的命名并不重要。HLists 可以命名为 HTuples。不同之处在于，在 Scala+Haskell 中，您可以使用元组（使用 Scala 语法）执行此操作：

def append2[A,B,C](in: (A,B), v: C) : (A,B,C) = (in._1, in._2, v)

to take an input tuple of exactly two elements of any type, append a third element, and return a fully typed tuple with exactly three elements. But while this is completely generic over types, it has to explicitly specify the input/output lengths.

取任何类型的正好两个元素的输入元组，附加第三个元素，并返回一个完全类型的元组，其中正好有三个元素。但是，虽然这对于类型来说是完全通用的，但它必须明确指定输入/输出长度。

What a Haskell style HList lets you do is make this generic over length, so you can append to any length of tuple/list and get back a fully statically typed tuple/list. This benefit also applies to homogeneously typed collections where you can append an int to a list of exactly n ints and get back a list that is statically typed to have exactly (n+1) ints without explicitly specifying n.

Haskell 风格的 HList 允许你做的是使这个泛型超长，这样你就可以附加到任何长度的元组/列表并返回一个完全静态类型的元组/列表。这种好处也适用于同构类型的集合，您可以在其中将一个 int 附加到一个恰好包含 n 个 int 的列表中，并返回一个静态类型化为恰好具有 (n+1) 个 int 的列表，而无需明确指定 n。