Haskell's newtypes in Scala - scala

In Haskell we can declare newtypes to reduce dynamic memory allocations and create type-safe APIs.
newtype Username String = Username String
deriving (Eq, Ord)
newtype works only with data types which have single constructor with single argument. Is there something similar to newtype in Scala?
Example:
case class Username(username: String)
for username we could've write something like this in Scala:
newtype Username(username: String)

The equivalent to Haskell's newtype are Opaque Type Aliases in Scala 3:
opaque type Username = String
It's basically a type alias … but opaque. Just like it says on the cover.

Related

Shapeless Witness and how it can give the actual singleton type

I'm trying to understand singleton types in shapeless and faced misunderstanding about singleton types compile-time type. Here is an example:
val x: Witness.`120`.T = 120.narrow
It works fine, but this constructions looks very unusual. What is Witness.120? In IDE it points to some macro function selectDynamic:
def selectDynamic(tpeSelector: String): Any = macro SingletonTypeMacros.witnessTypeImpl
which has compile-time type Any and judging by the construction Witness.120.T a type member T. This looks like magic... Can anyone give some explanation on what actually is going on when one writes something like:
val x: Witness.`120`.T = //...
Witness creates a so-called literal-based singleton type. Literal type means it's a type that can only accept one value.
So if you create a function like this:
def f(x: Witness.`120`.T) = x
it would accept only integer 120, but not 121.
Since Scala 2.13 literal types are integrated into the language, so you can write it simply as:
def f(x: 120) = x
Function narrow narrows type of value 120 from general Int to literal 120.

Benefits of creating a type alias as oppose to using a String

I can see a few benefits of creating a custom type over using a string for things like:
type UserId = String
def getUser(userId: UserId)...
versus:
def getUser(userId: String)...
It makes your code more readable, and I imagine if you ever need to change the type from a String to a Int it would make refactoring easier.
What other benefits are there?
While using type can improve readability in some cases, if you use it to create an alias it won't make your code safer or easier to refactor. Consider:
type A = String
def m(s: A) = s.length
m("12345") // It's "safe" to use String instead of A
If you want a wrapper so you don't pass e.g. user login where user name is expected (both strings), you can use a value class:
class UserName(val name: String) extends AnyVal
def m(name: UserName) = name.name.length
m("12345") //> error: type mismatch
m(new UserName("12345")) //> 5
Value classes have a very small footprint, in fact they operate with their underlying object directly. If you look at the generated code it will in fact be:
def m(name: String): Int = name.length();
m("12345")
type shines when you need to create type expressions, e.g.:
type ¬[A] = A => Nothing
type ¬¬[A] = ¬[¬[A]]
type ∨[T, U] = ¬[¬[T] with ¬[U]]
type |∨|[T, U] = { type λ[X] = ¬¬[X] <:< (T ∨ U) }
(the first thing which came my mind, credit to Miles Sabin)
when you build your own library, you would like to expose nice DSL to work with your library. sometimes it is done by implicits to create infix operators. you can take a look at : infix operator
when you create implicit for your type it wouldn't happen for String, unless you convert that string to your type.
whats the value ? safety when you use implicits.

scala.Null clarification

Want to clarify about scala.Null. As I know scala.Null has instance null and class. For example if write like this
val x: Null = null
Type inference set type for the x Null.
According Scala classes hierarhy "please see image" Scala cannot use variables without wrappers like Int, Double, etc. That is why we can found Null for the type inference mechanism resolving. Is it correct vision ?
Scala classes hierarhy
You seem to be mixing some of these concepts:
Type Inference is the ability of the compiler to infer the type when the code doesn't explicitly state it. In your example - you do state the type, and that type is Null - no inference here:
val x: Null = null
Here's a simple example of type inference:
scala> val whoKnows = 12
whoKnows: Int = 12
Compiler inferred the type Int since we assigned the value 12, which is an integer. There's much more to it (see http://docs.scala-lang.org/tutorials/tour/local-type-inference), but that's the basics.
null can be used in Scala just like in Java (although it's very much frowned upon, as Scala offers many safer alternatives, mainly None), for example:
scala> val nullStr: String = null
nullStr: String = null
scala> val nullList: List[Int] = null
nullList: List[Int] = null
Where can't null be used? Just like in Java - for "primitives" like int, double etc. In Scala, there's no such thing as a primitive, but there's still a difference between these "value" types (named with upper-case like other types, e.g. Int, Double) and other types: value types share the common trait AnyVal, whereas all other types share the trait AnyRef - to signify, among other things, this difference.
As for what the Null trait is good for - see Usages of Null / Nothing / Unit in Scala
The type Null in Scala is a special type. What's special about it is that it is a subtype of all reference types - it's a subtype of every type that is a subtype of AnyRef.
The reason for that is to make it possible to assign the value null to any reference type.
Note that besides reference types, Scala also has value types. These are the types that are subtypes of AnyVal. Examples of value types are the built-in types that map to the primitive types of the JVM: Byte, Short, Int, Long, Float, Double, Boolean, and Char, and also the type Unit.
Note that AnyVal and its subtypes are not subtypes of AnyRef. You can't assign null to a variable of a value type.
Note that the value types Int, Double etc. are not like Java's wrapper types (java.lang.Integer, java.lang.Double etc.). When you use the value types, there is no boxing and unboxing going on to/from objects. These value types directly map to the primitive types of the JVM. Therefore you cannot assign null to a variable of one of those types.
In other words: types like Int and Double are not wrappers, they directly represent primitive types.

What's the difference between "Generic type" and "Higher-kinded type"?

I found myself really can't understand the difference between "Generic type" and "higher-kinded type".
Scala code:
trait Box[T]
I defined a trait whose name is Box, which is a type constructor that accepts a parameter type T. (Is this sentence correct?)
Can I also say:
Box is a generic type
Box is a higher-kinded type
None of above is correct
When I discuss the code with my colleagues, I often struggle between the word "generic" and "higher-kinde" to express it.
It's probably too late to answer now, and you probably know the difference by now, but I'm going to answer just to offer an alternate perspective, since I'm not so sure that what Greg says is right. Generics is more general than higher kinded types. Lots of languages, such as Java and C# have generics, but few have higher-kinded types.
To answer your specific question, yes, Box is a type constructor with a type parameter T. You can also say that it is a generic type, although it is not a higher kinded type. Below is a broader answer.
This is the Wikipedia definition of generic programming:
Generic programming is a style of computer programming in which algorithms are written in terms of types to-be-specified-later that are then instantiated when needed for specific types provided as parameters. This approach, pioneered by ML in 1973,1 permits writing common functions or types that differ only in the set of types on which they operate when used, thus reducing duplication.
Let's say you define Box like this. It holds an element of some type, and has a few special methods. It also defines a map function, something like Iterable and Option, so you can take a box holding an integer and turn it into a box holding a string, without losing all those special methods that Box has.
case class Box(elem: Any) {
..some special methods
def map(f: Any => Any): Box = Box(f(elem))
}
val boxedNum: Box = Box(1)
val extractedNum: Int = boxedString.elem.asInstanceOf[Int]
val boxedString: Box = boxedNum.map(_.toString)
val extractedString: String = boxedString.elem.asInstanceOf[String]
If Box is defined like this, your code would get really ugly because of all the calls to asInstanceOf, but more importantly, it's not typesafe, because everything is an Any.
This is where generics can be useful. Let's say we define Box like this instead:
case class Box[A](elem: A) {
def map[B](f: A => B): Box[B] = Box(f(elem))
}
Then we can use our map function for all kinds of stuff, like changing the object inside the Box while still making sure it's inside a Box. Here, there's no need for asInstanceOf since the compiler knows the type of your Boxes and what they hold (even the type annotations and type arguments are not necessary).
val boxedNum: Box[Int] = Box(1)
val extractedNum: Int = boxedNum.elem
val boxedString: Box[String] = boxedNum.map[String](_.toString)
val extractedString: String = boxedString.elem
Generics basically lets you abstract over different types, letting you use Box[Int] and Box[String] as different types even though you only have to create one Box class.
However, let's say that you don't have control over this Box class, and it's defined merely as
case class Box[A](elem: A) {
//some special methods, but no map function
}
Let's say this API you're using also defines its own Option and List classes (both accepting a single type parameter representing the type of the elements). Now you want to be able to map over all these types, but since you can't modify them yourself, you'll have to define an implicit class to create an extension method for them. Let's add an implicit class Mappable for the extension method and a typeclass Mapper.
trait Mapper[C[_]] {
def map[A, B](context: C[A])(f: A => B): C[B]
}
implicit class Mappable[C[_], A](context: C[A])(implicit mapper: Mapper[C]) {
def map[B](f: A => B): C[B] = mapper.map(context)(f)
}
You could define implicit Mappers like so
implicit object BoxMapper extends Mapper[Box] {
def map[B](box: Box[A])(f: A => B): Box[B] = Box(f(box.elem))
}
implicit object OptionMapper extends Mapper[Option] {
def map[B](opt: Option[A])(f: A => B): Option[B] = ???
}
implicit object ListMapper extends Mapper[List] {
def map[B](list: List[A])(f: A => B): List[B] = ???
}
//and so on
and use it as if Box, Option, List, etc. have always had map methods.
Here, Mappable and Mapper are higher-kinded types, whereas Box, Option, and List are first-order types. All of them are generic types and type constructors. Int and String, however, are proper types. Here are their kinds, (kinds are to types as types are to values).
//To check the kind of a type, you can use :kind in the REPL
Kind of Int and String: *
Kind of Box, Option, and List: * -> *
Kind of Mappable and Mapper: (* -> *) -> *
Type constructors are somewhat analogous to functions (which are sometimes called value constructors). A proper type (kind *) is analogous to a simple value. It's a concrete type that you can use for return types, as the types of your variables, etc. You can just directly say val x: Int without passing Int any type parameters.
A first-order type (kind * -> *) is like a function that looks like Any => Any. Instead of taking a value and giving you a value, it takes a type and gives you another type. You can't use first-order types directly (val x: List won't work) without giving them type parameters (val x: List[Int] works). This is what generics does - it lets you abstract over types and create new types (the JVM just erases that information at runtime, but languages like C++ literally generate new classes and functions). The type parameter C in Mapper is also of this kind. The underscore type parameter (you could also use something else, like x) lets the compiler know that C is of kind * -> *.
A higher-kinded type/higher-order type is like a higher-order function - it takes another type constructor as a parameter. You can't use a Mapper[Int] above, because C is supposed to be of kind * -> * (so that you can do C[A] and C[B]), whereas Int is merely *. It's only in languages like Scala and Haskell with higher-kinded types that you can create types like Mapper above and other things beyond languages with more limited type systems, like Java.
This answer (and others) on a similar question may also help.
Edit: I've stolen this very helpful image from that same answer:
There is no difference between 'Higher-Kinded Types' and 'Generics'.
Box is a 'structure' or 'context' and T can be any type.
So T is generic in the English sense... we don't know what it will be and we don't care because we aren't going to be operating on T directly.
C# also refers to these as Generics. I suspect they chose this language because of its simplicity (to not scare people away).

Pattern matching on List[T] and Set[T] in Scala vs. Haskell: effects of type erasure

Would the Haskell equivalent of the code below produce correct answers?
Can this Scala code be fixed to produce correct answers ? If yes, how ?
object TypeErasurePatternMatchQuestion extends App {
val li=List(1,2,3)
val ls=List("1","2","3")
val si=Set(1,2,3)
val ss=Set("1","2","3")
def whatIsIt(o:Any)=o match{
case o:List[Int] => "List[Int]"
case o:List[String] => "List[String]"
case o:Set[Int] => "Set[Int]"
case o:Set[String] => "Set[String]"
}
println(whatIsIt(li))
println(whatIsIt(ls))
println(whatIsIt(si))
println(whatIsIt(ss))
}
prints:
List[Int]
List[Int]
Set[Int]
Set[Int]
but I would expect it to print:
List[Int]
List[String]
Set[Int]
Set[String]
You must understand that by saying o:Any you erase all the specific information about the type and further on the type Any is all that the compiler knows about value o. That's why from that point on you can only rely on the runtime information about the type.
The case-expressions like case o:List[Int] are resolved using the JVM's special instanceof runtime mechanism. However the buggy behaviour you experience is caused by this mechanism only taking the first-rank type into account (the List in List[Int]) and ignoring the parameters (the Int in List[Int]). That's why it treats List[Int] as equal to List[String]. This issue is known as "Generics Erasure".
Haskell on the other hand performs a complete type erasure, which is well explained in the answer by Ben.
So the problem in both languages is the same: we need to provide a runtime information about the type and its parameters.
In Scala you can achieve that using the "reflection" library, which resolves that information implicitly:
import reflect.runtime.{universe => ru}
def whatIsIt[T](o : T)(implicit t : ru.TypeTag[T]) =
if( t.tpe <:< ru.typeOf[List[Int]] )
"List[Int]"
else if ( t.tpe <:< ru.typeOf[List[String]] )
"List[String]"
else if ( t.tpe <:< ru.typeOf[Set[Int]] )
"Set[Int]"
else if ( t.tpe <:< ru.typeOf[Set[String]] )
"Set[String]"
else sys.error("Unexpected type")
println(whatIsIt(List("1","2","3")))
println(whatIsIt(Set("1","2","3")))
Output:
List[String]
Set[String]
Haskell has a very different approach to polymorphism. Above all, it does not have subtype polymorphism (it's not a weakness though), that's why the type-switching pattern matches as in your example are simply irrelevant. However it is possible to translate the Scala solution from above into Haskell quite closely:
{-# LANGUAGE MultiWayIf, ScopedTypeVariables #-}
import Data.Dynamic
import Data.Set
whatIsIt :: Dynamic -> String
whatIsIt a =
if | Just (_ :: [Int]) <- fromDynamic a -> "[Int]"
| Just (_ :: [String]) <- fromDynamic a -> "[String]"
| Just (_ :: Set Int) <- fromDynamic a -> "Set Int"
| Just (_ :: Set String) <- fromDynamic a -> "Set String"
| otherwise -> error "Unexpected type"
main = do
putStrLn $ whatIsIt $ toDyn ([1, 2, 3] :: [Int])
putStrLn $ whatIsIt $ toDyn (["1", "2", "3"] :: [String])
putStrLn $ whatIsIt $ toDyn (Data.Set.fromList ["1", "2", "3"] :: Set String)
Output:
[Int]
[String]
Set String
However I must outline boldly that this is far from a typical scenario of Haskell programming. The language's type-system is powerful enough to solve extremely intricate problems while maintaining all the type-level information (and safety). Dynamic is only used in very special cases in low-level libraries.
GHC does even more type erasure than the JVM; at runtime the types are completely gone (not just the type parameters).
Haskell's approach to types is to use them at compile time to guarantee that no ill-typed operation can ever be carried out, and since Haskell doesn't have OO-style subtyping and dynamic dispatch, there's no purpose at all to keeping the types around. So data is compiled to a memory structure that simply contains the right values, and functions are compiled with baked-in knowledge of the structure of the types on which they operate1, and just blindly expect their arguments to have that structure. That's why you get fun things like segmentation faults if you mess with unsafeCoerce incorrectly, not just a runtime exception saying the value was not of the expected type; at runtime Haskell has no idea whether a value is of any given type.
So rather than Haskell giving "the right answer" to the equivalent program, Haskell disallows your program as unsafe! There is no Any type in Haskell to which you can cast whatever you want.
That's not 100% true; in both Haskell and Scala there are ways of keeping type information alive at runtime. Essentially it's done by creating ordinary data structures that represent types, and passing them around together values that are of those types, so at runtime you can refer to the type representation object for information about the type of the other object. There are library and language facilities in both languages to let you use this mechanism at a higher (and more principled) level, so that it's easier to use safely. Because it requires the type tokens to be passed around, you have to "opt-in" to such features, and your callers have to be aware of it to pass you the required type tokens (whether the actual generation and passing of the token is done implicitly or explicitly).
Without using such features, Haskell provides no way to pattern match on a value that could be of type List Int or Set String to find out which one it is. Either you're using a monomorphic type, in which case it can only be one type and the others will be rejected, or you're using a polymorphic type, in which case you can only apply code to it that will do the same thing2 regardless of which concrete type instantiates the polymorphic type.
1 Except for polymorphic functions, which assume nothing about their polymorphic arguments, and so can basically do nothing with them except pass them to other polymorphic functions (with matching type class constraints, if any).
2 Type class constrained polymorphic types are the only exception to this. Even then, if you've got a value a type that's a member of some type class, all you can do with it is pass it to other functions that accept values in any type that is a member of that type class. And if those functions are general functions defined outside of the type class in question, they'll be under the same restriction. It's only the type class methods themselves that can actually "do something different" for different types in the class, and that's because they are the union of a whole bunch of monomorphic definitions that operate on one particular type in the class. You can't write code that gets to take a polymorphic value, inspect it to see what it was instantiated with, and then decide what to do.
Of course Haskell prints the right answer:
import Data.Set
import Data.Typeable
main = do
let li=[1,2,3]
let ls=["1","2","3"]
let si=Data.Set.fromList[1,2,3]
let ss=Data.Set.fromList["1","2","3"]
print $ typeOf li
print $ typeOf ls
print $ typeOf si
print $ typeOf ss
prints
[Integer]
[[Char]]
Set Integer
Set [Char]