SlideShare una empresa de Scribd logo
1 de 22
Descargar para leer sin conexión
• Explore a terser definition of the Option Monad that uses a Scala 3 enum as an Algebraic Data Type.
• In the process, have a tiny bit of fun with Scala 3 enums.
• Get a refresher on the Functor and Monad laws.
• See how easy it is to use Scala 3 extension methods, e.g. to add convenience methods and infix operators.
@philip_schwarzslides by
https://www.slideshare.net/pjschwarz
enum for a terser Option
Monad Algebraic Data Type..…
We introduce a new type, Option. As we mentioned earlier, this type also exists in the
Scala standard library, but we’re re-creating it here for pedagogical purposes:
sealed trait Option[+A]
case class Some[+A](get: A) extends Option[A]
case object None extends Option[Nothing]
Option is mandatory! Do not use null to denote that an optional value is absent. Let’s have a
look at how Option is defined:
sealed abstract class Option[+A] extends IterableOnce[A]
final case class Some[+A](value: A) extends Option[A]
case object None extends Option[Nothing]
Since creating new data types is so cheap, and it is possible to work with them
polymorphically, most functional languages define some notion of an optional value. In
Haskell it is called Maybe, in Scala it is Option, … Regardless of the language, the
structure of the data type is similar:
data Maybe a = Nothing –- no value
| Just a -- holds a value
sealed abstract class Option[+A] // optional value
case object None extends Option[Nothing] // no value
case class Some[A](value: A) extends Option[A] // holds a value
We have already encountered scalaz’s improvement over scala.Option, called Maybe. It is
an improvement because it does not have any unsafe methods like Option.get, which can
throw an exception, and is invariant.
It is typically used to represent when a thing may be present or not without giving any extra
context as to why it may be missing.
sealed abstract class Maybe[A] { ... }
object Maybe {
final case class Empty[A]() extends Maybe[A]
final case class Just[A](a: A) extends Maybe[A]
Over the years we have all got very used to
the definition of the Option monad’s
Algebraic Data Type (ADT).
With the arrival of Scala 3 however, the definition of the
Option ADT becomes much terser thanks to the fact that it
can be implemented using the new enum concept .
OK, so this is, again, cool, now we have parity with Java, but we can actually go way further. enums can not
only have value parameters, they also can have type parameters, like this.
So you can have an enum Option with a covariant type parameter T and then two cases Some and None.
So that of course gives you what people call an Algebraic Data Type, or ADT.
Scala so far was lacking a simple way to write an ADT. What you had to do is essentially what the compiler
would translate this to.
A Tour of Scala 3 – by Martin Odersky
Martin Odersky
@odersky
So the compiler would take this ADT that you have seen here and translate it into essentially this:
And so far, if you wanted something like that, you would have written essentially the same thing. So a sealed
abstract class or a sealed abstract trait, Option, with a case class as one case, and as the other case, here it is
a val, but otherwise you could also use a case object.
And that of course is completely workable, but it is kind of tedious. When Scala started, one of the main
motivations, was to avoid pointless boilerplate. So that’s why case classes were invented, and a lot of other
innovations that just made code more pleasant to write and more compact than Java code, the standard at
the time.
A Tour of Scala 3 – by Martin Odersky
Martin Odersky
@odersky
enum Option[+A]:
case Some(a: A)
case None
On the next slide we have a go at
adding some essential methods to
this terser enum-based Option ADT.
@philip_schwarz
enum Option[+A]:
case Some(a: A)
case None
def map[B](f: A => B): Option[B] =
this match
case Some(a) => Some(f(a))
case None => None
def flatMap[B](f: A => Option[B]): Option[B] =
this match
case Some(a) => f(a)
case None => None
def fold[B](ifEmpty: => B)(f: A => B) =
this match
case Some(a) => f(a)
case None => ifEmpty
def filter(p: A => Boolean): Option[A] =
this match
case Some(a) if p(a) => Some(a)
case _ => None
def withFilter(p: A => Boolean): Option[A] =
filter(p)
object Option :
def pure[A](a: A): Option[A] = Some(a)
def none: Option[Nothing] = None
extension[A](a: A):
def some: Option[A] = Some(a)
Option is a monad, so we have given it a
flatMap method and a pure method. In Scala
the latter is not strictly needed, but we’ll make
use of it later.
Every monad is also a functor, and this is
reflected in the fact that we have given Option a
map method.
We gave Option a fold method, to allow us to
interpret/execute the Option effect, i.e. to
escape from the Option container, or as John a
De Goes puts it, to translate away from
optionality by providing a default value.
We want our Option to integrate with for
comprehensions sufficiently well for our current
purposes, so in addition to map and flatMap
methods, we have given it a simplistic withFilter
method that is just implemented in terms of
filter, another pretty essential method.
There are of course many many other methods
that we would normally want to add to Option.
The some and none methods
are just there to provide the
convenience of Cats-like syntax
for lifting a pure value into an
Option and for referring to the
empty Option instance.
Yes, the some method on the previous slide was implemented
using the new Scala 3 feature of Extension Methods.
On the next slide we do the following:
• See our Option monad ADT again
• Define a few enumerated types using use the Scala 3 enum feature.
• Add a simple program showing the Option monad in action.
enum Option[+A]:
case Some(a: A)
case None
def map[B](f: A => B): Option[B] =
this match
case Some(a) => Some(f(a))
case None => None
def flatMap[B](f: A => Option[B]): Option[B] =
this match
case Some(a) => f(a)
case None => None
def fold[B](zero: => B)(f: A => B) =
this match
case Some(a) => f(a)
case None => zero
def filter(p: A => Boolean): Option[A] =
this match
case Some(a) if p(a) => Some(a)
case _ => None
def withFilter(p: A => Boolean): Option[A] =
filter(p)
object Option :
def pure[A](a: A): Option[A] = Some(a)
def none: Option[Nothing] = None
extension[A](a: A):
def some: Option[A] = Some(a)
enum Greeting(val language: Language):
override def toString: String =
s"${enumLabel} ${language.toPreposition}"
case Welcome extends Greeting(English)
case Willkommen extends Greeting(German)
case Bienvenue extends Greeting(French)
case Bienvenido extends Greeting(Spanish)
case Benvenuto extends Greeting(Italian)
enum Language(val toPreposition: String):
case English extends Language("to")
case German extends Language("nach")
case French extends Language("à")
case Spanish extends Language("a")
case Italian extends Language("a")
enum Planet:
case Mercury, Venus, Earth, Mars, Jupiter, Saturn, Neptune, Uranus, Pluto, Scala3
case class Earthling(name: String, surname: String, languages: Language*)
def greet(maybeGreeting: Option[Greeting],
maybeEarthling: Option[Earthling],
maybePlanet: Option[Planet]): Option[String] =
for
greeting <- maybeGreeting
earthling <- maybeEarthling
planet <- maybePlanet
if earthling.languages contains greeting.language
yield s"$greeting $planet ${earthling.name}!"
@main def main =
val maybeGreeting =
greet( maybeGreeting = Some(Welcome),
maybeEarthling = Some(Earthling("Fred", "Smith", English, Italian)),
maybePlanet = Some(Scala3))
println(maybeGreeting.fold("Error: no greeting message")
(msg => s"*** $msg ***"))
*** Welcome to Scala3 Fred! ***
def greet(maybeGreeting: Option[Greeting],
maybeEarthling: Option[Earthling],
maybePlanet: Option[Planet]): Option[String] =
for
greeting <- maybeGreeting
earthling <- maybeEarthling
planet <- maybePlanet
if earthling.languages contains greeting.language
yield s"$greeting $planet ${earthling.name}!"
// Greeting Earthling Planet Greeting Message
assert(greet(Some(Welcome), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == Some("Welcome to Scala3 Fred!"))
assert(greet(Some(Benvenuto), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == Some("Benvenuto a Scala3 Fred!"))
assert(greet(Some(Bienvenue), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == None)
assert(greet(None, Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == None)
assert(greet(Some(Welcome), None, Some(Scala3)) == None)
assert(greet(Some(Welcome), Some(Earthling("Fred", "Smith", English, Italian)), None) == None)
assert(greet(Welcome.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == ("Welcome to Scala3 Fred!").some)
assert(greet(Benvenuto.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == ("Benvenuto a Scala3 Fred!").some)
assert(greet(Bienvenue.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == none)
assert(greet(none, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == none)
assert(greet(Welcome.some, none, Scala3.some) == none)
assert(greet(Welcome.some, Earthling("Fred", "Smith", English, Italian).some, none) == none)
Same again, but this time using the some and none convenience methods.
Below are some tests
for our simple program.
@philip_schwarz
val stringToInt: String => Option[Int] = s =>
Try { s.toInt }.fold(_ => None, Some(_))
assert( stringToInt("123") == Some(123) )
assert( stringToInt("1x3") == None )
assert( intToChars(123) == Some(List('1', '2', '3')))
assert( intToChars(0) == Some(List('0')))
assert( intToChars(-10) == None)
assert(charsToInt(List('1', '2', '3')) == Some(123) )
assert(charsToInt(List('1', 'x', '3')) == None )
val intToChars: Int => Option[List[Char]] = n =>
if n < 0 then None
else Some(n.toString.toArray.toList)
val charsToInt: Seq[Char] => Option[Int] = chars =>
Try {
chars.foldLeft(0){ (n,char) => 10 * n + char.toString.toInt }
}.fold(_ => None, Some(_))
def doublePalindrome(s: String): Option[String] =
for
n <- stringToInt(s)
chars <- intToChars(2 * n)
palindrome <- charsToInt(chars ++ chars.reverse)
yield palindrome.toString
assert( doublePalindrome("123") == Some("246642") )
assert( doublePalindrome("1x3") == None )
The remaining slides provide us with a refresher of the functor and monad laws. To do so, they use two examples of ordinary functions and three
examples of Kleisli arrows, i.e. functions whose signature is of the form A => F[B], for some monad F, which in our case is the Option monad.
The example functions are defined below, together with a function that uses them. While the functions are bit contrived, they do the job.
The reason why the Kleisli arrows are a bit more complex than would normally be expected is that since in this slide deck we are defining our own
simple Option monad, we are not taking shortcuts that involve the standard Scala Option, e.g. converting a String to an Int using the toIntOption
function available on String.
val double: Int => Int = n => 2 * n
val square: Int => Int = n => n * n
Since every monad is also a functor, the next slide is a
reminder of the functor laws.
We also define a Scala 3 extension method to provide
syntax for the infix operator for function composition.
// FUNCTOR LAWS
// identity law: ma map identity = identity(ma)
assert( (f(a) map identity) == identity(f(a)) )
assert( (a.some map identity) == identity(a.some) )
assert( (none map identity) == identity(none) )
// composition law: ma map (g ∘ h) == ma map h map g
assert( (f(a) map (g ∘ h)) == (f(a) map h map g) )
assert( (3.some map (g ∘ h)) == (3.some map h map g) )
assert( (none map (g ∘ h)) == (none map h map g) )
val f = stringToInt
val g = double
val h = square
val a = "123"
// plain function composition
extension[A,B,C](f: B => C)
def ∘ (g: A => B): A => C =
a => f(g(a))
def identity[A](x: A): A = x
enum Option[+A]:
case Some(a: A)
case None
def map[B](f: A => B): Option[B] =
this match
case Some(a) => Some(f(a))
case None => None
...
object Option :
def pure[A](a: A): Option[A] = Some(a)
def none: Option[Nothing] = None
extension[A](a: A):
def some: Option[A] = Some(a)
assert( stringToInt("123") == Some(123) )
assert( stringToInt("1x3") == None )
val double: Int => Int = n => 2 * n
val square: Int => Int = n => n * n
// FUNCTOR LAWS
// identity law: ma map identity = identity(ma)
assert( (f(a) map identity) == identity(f(a)) )
assert( (a.some map identity) == identity(a.some) )
assert( (none map identity) == identity(none) )
// composition law: ma map (g ∘ h) == ma map h map g
assert( (f(a) map (g ∘ h)) == (f(a) map h map g) )
assert( (3.some map (g ∘ h)) == (3.some map h map g) )
assert( (none map (g ∘ h)) == (none map h map g) )
val f = stringToInt
val g = double
val h = square
val a = "123"
// plain function composition
extension[A,B,C](f: B => C)
def ∘ (g: A => B): A => C =
a => f(g(a))
def identity[A](x: A): A = x
enum Option[+A]:
case Some(a: A)
case None
def map[B](f: A => B): Option[B] =
this match
case Some(a) => Some(f(a))
case None => None
...
object Option :
def pure[A](a: A): Option[A] = Some(a)
def none: Option[Nothing] = None
extension[A](a: A):
def some: Option[A] = Some(a)
assert( stringToInt("123") == Some(123) )
assert( stringToInt("1x3") == None )
val double: Int => Int = n => 2 * n
val square: Int => Int = n => n * n
@philip_schwarz
While the functor Identity Law is very simple, the fact that it can be formulated in slightly
different ways can sometimes be a brief source of puzzlement when recalling the law.
On the next slide I have a go at recapping three different ways of formulating the law.
F(idX) = idF(X) fmap id = id
fmapMaybe ida x = idMaybe a x
Option(idX) = idOption(X)
x map (a => a) = x
mapOption(idX) = idOption(X)
x mapOption (idX) = idOption(X)(x)
fmapF ida = idF a
fmapMaybe ida = idMaybe a
λ> :type fmap
fmap :: Functor f => (a -> b) -> f a -> f b
λ> inc x = x + 1
λ> fmap inc (Just 3)
Just 4
λ> fmap inc Nothing
Nothing
λ> :type id
id :: a -> a
λ> id 3
3
λ> id (Just 3)
Just 3
λ> fmap id Just 3 == id Just 3
True
λ> fmap id Nothing == id Nothing
True
scala> :type Option(3).map
(Int => Any) => Option[Any]
scala> val inc: Int => Int = n => n + 1
scala> Some(3) map inc
val res1: Option[Int] = Some(4)
scala> None map inc
val res2: Option[Int] = None
scala> :type identity
Any => Any
scala> identity(3)
val res3: Int = 3
scala> identity(Some(3))
val res4: Some[Int] = Some(3)
scala> (Some(3) map identity) == identity(Some(3))
val res10: Boolean = true
scala> (None map identity) == identity(None)
val res11: Boolean = true
Functor
Option Maybe
x map identity = identity(x) fmap id x = id x
Category TheoryScala Haskell
Some, None Just, Nothing
Functor Identity Law
The last two slides of this deck remind us of the monad laws.
They also make use of Scala 3 extension methods, this time to provide
syntax for the infix operators for flatMap and Kleisli composition.
// MONAD LAWS
// left identity law: pure(a) flatMap f == f(a)
assert( (pure(a) flatMap f) == f(a) )
// right identity law: ma flatMap pure == ma
assert( (f(a) flatMap pure) == f(a) )
assert( (a.some flatMap pure) == a.some )
assert( (none flatMap pure) == none )
// associativity law: ma flatMap f flatMap g = ma flatMap (a => f(a) flatMap g)
assert( ((f(a) flatMap g) flatMap h) == (f(a) flatMap (x => g(x) flatMap h)) )
assert( ((3.some flatMap g) flatMap h) == (3.some flatMap (x => g(x) flatMap h)) )
assert( ((none flatMap g) flatMap h) == (none flatMap (x => g(x) flatMap h)) )
enum Option[+A]:
case Some(a: A)
case None
...
def flatMap[B](f: A => Option[B]): Option[B] =
this match
case Some(a) => f(a)
case None => None
...
object Option :
def pure[A](a: A): Option[A] = Some(a)
def none: Option[Nothing] = None
def id[A](oa: Option[A]): Option[A] = oa
extension[A](a: A):
def some: Option[A] = Some(a)
val f = stringToInt
val g = intToChars
val h = charsToInt
val a = "123”
assert( stringToInt("123") == Some(123) )
assert( stringToInt("1x3") == None )
assert( intToChars(123) == Some(List('1', '2', '3')))
assert( intToChars(0) == Some(List('0')))
assert( intToChars(-10) == None)
assert(charsToInt(List('1', '2', '3')) == Some(123) )
assert(charsToInt(List('1', 'x', '3')) == None )
The monad laws again, but this time using a
Haskell-style bind operator as an alias for flatMap.
And here are the monad laws expressed in
terms of Kleisli composition (the fish operator).
If you are new to functor laws and/or monad laws you might want to take a look at some of the following
https://www2.slideshare.net/pjschwarz/functor-laws
https://www2.slideshare.net/pjschwarz/monad-laws-must-be-checked-107011209
https://www2.slideshare.net/pjschwarz/rob-norrisfunctionalprogrammingwitheffects
That’s all. I hope you found it useful.
@philip_schwarz

Más contenido relacionado

La actualidad más candente

Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...Philip Schwarz
 
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1Philip Schwarz
 
The Expression Problem - Part 1
The Expression Problem - Part 1The Expression Problem - Part 1
The Expression Problem - Part 1Philip Schwarz
 
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2Philip Schwarz
 
Applicative Functor - Part 3
Applicative Functor - Part 3Applicative Functor - Part 3
Applicative Functor - Part 3Philip Schwarz
 
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...Philip Schwarz
 
Big picture of category theory in scala with deep dive into contravariant and...
Big picture of category theory in scala with deep dive into contravariant and...Big picture of category theory in scala with deep dive into contravariant and...
Big picture of category theory in scala with deep dive into contravariant and...Piotr Paradziński
 
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3Philip Schwarz
 
Sequence and Traverse - Part 2
Sequence and Traverse - Part 2Sequence and Traverse - Part 2
Sequence and Traverse - Part 2Philip Schwarz
 
Ad hoc Polymorphism using Type Classes and Cats
Ad hoc Polymorphism using Type Classes and CatsAd hoc Polymorphism using Type Classes and Cats
Ad hoc Polymorphism using Type Classes and CatsPhilip Schwarz
 
‘go-to’ general-purpose sequential collections - from Java To Scala
‘go-to’ general-purpose sequential collections -from Java To Scala‘go-to’ general-purpose sequential collections -from Java To Scala
‘go-to’ general-purpose sequential collections - from Java To ScalaPhilip Schwarz
 
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and Scala
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and ScalaSierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and Scala
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and ScalaPhilip Schwarz
 
Real World Haskell: Lecture 6
Real World Haskell: Lecture 6Real World Haskell: Lecture 6
Real World Haskell: Lecture 6Bryan O'Sullivan
 
Monad Laws Must be Checked
Monad Laws Must be CheckedMonad Laws Must be Checked
Monad Laws Must be CheckedPhilip Schwarz
 
The Functional Programming Triad of Folding, Scanning and Iteration - a first...
The Functional Programming Triad of Folding, Scanning and Iteration - a first...The Functional Programming Triad of Folding, Scanning and Iteration - a first...
The Functional Programming Triad of Folding, Scanning and Iteration - a first...Philip Schwarz
 
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...Quicksort - a whistle-stop tour of the algorithm in five languages and four p...
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...Philip Schwarz
 
Functional Core and Imperative Shell - Game of Life Example - Haskell and Scala
Functional Core and Imperative Shell - Game of Life Example - Haskell and ScalaFunctional Core and Imperative Shell - Game of Life Example - Haskell and Scala
Functional Core and Imperative Shell - Game of Life Example - Haskell and ScalaPhilip Schwarz
 
Sequence and Traverse - Part 3
Sequence and Traverse - Part 3Sequence and Traverse - Part 3
Sequence and Traverse - Part 3Philip Schwarz
 

La actualidad más candente (20)

Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part ...
 
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1
Scala 3 by Example - Algebraic Data Types for Domain Driven Design - Part 1
 
The Expression Problem - Part 1
The Expression Problem - Part 1The Expression Problem - Part 1
The Expression Problem - Part 1
 
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2
Folding Unfolded - Polyglot FP for Fun and Profit - Haskell and Scala - Part 2
 
Applicative Functor - Part 3
Applicative Functor - Part 3Applicative Functor - Part 3
Applicative Functor - Part 3
 
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...
Game of Life - Polyglot FP - Haskell, Scala, Unison - Part 2 - with minor cor...
 
Big picture of category theory in scala with deep dive into contravariant and...
Big picture of category theory in scala with deep dive into contravariant and...Big picture of category theory in scala with deep dive into contravariant and...
Big picture of category theory in scala with deep dive into contravariant and...
 
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3
Game of Life - Polyglot FP - Haskell - Scala - Unison - Part 3
 
Sequence and Traverse - Part 2
Sequence and Traverse - Part 2Sequence and Traverse - Part 2
Sequence and Traverse - Part 2
 
Ad hoc Polymorphism using Type Classes and Cats
Ad hoc Polymorphism using Type Classes and CatsAd hoc Polymorphism using Type Classes and Cats
Ad hoc Polymorphism using Type Classes and Cats
 
‘go-to’ general-purpose sequential collections - from Java To Scala
‘go-to’ general-purpose sequential collections -from Java To Scala‘go-to’ general-purpose sequential collections -from Java To Scala
‘go-to’ general-purpose sequential collections - from Java To Scala
 
Monads do not Compose
Monads do not ComposeMonads do not Compose
Monads do not Compose
 
State Monad
State MonadState Monad
State Monad
 
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and Scala
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and ScalaSierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and Scala
Sierpinski Triangle - Polyglot FP for Fun and Profit - Haskell and Scala
 
Real World Haskell: Lecture 6
Real World Haskell: Lecture 6Real World Haskell: Lecture 6
Real World Haskell: Lecture 6
 
Monad Laws Must be Checked
Monad Laws Must be CheckedMonad Laws Must be Checked
Monad Laws Must be Checked
 
The Functional Programming Triad of Folding, Scanning and Iteration - a first...
The Functional Programming Triad of Folding, Scanning and Iteration - a first...The Functional Programming Triad of Folding, Scanning and Iteration - a first...
The Functional Programming Triad of Folding, Scanning and Iteration - a first...
 
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...Quicksort - a whistle-stop tour of the algorithm in five languages and four p...
Quicksort - a whistle-stop tour of the algorithm in five languages and four p...
 
Functional Core and Imperative Shell - Game of Life Example - Haskell and Scala
Functional Core and Imperative Shell - Game of Life Example - Haskell and ScalaFunctional Core and Imperative Shell - Game of Life Example - Haskell and Scala
Functional Core and Imperative Shell - Game of Life Example - Haskell and Scala
 
Sequence and Traverse - Part 3
Sequence and Traverse - Part 3Sequence and Traverse - Part 3
Sequence and Traverse - Part 3
 

Similar a Scala 3 enum for a terser Option Monad Algebraic Data Type

The Great Scala Makeover
The Great Scala MakeoverThe Great Scala Makeover
The Great Scala MakeoverGarth Gilmour
 
Monoids - Part 2 - with examples using Scalaz and Cats
Monoids - Part 2 - with examples using Scalaz and CatsMonoids - Part 2 - with examples using Scalaz and Cats
Monoids - Part 2 - with examples using Scalaz and CatsPhilip Schwarz
 
Programming in Scala - Lecture Three
Programming in Scala - Lecture ThreeProgramming in Scala - Lecture Three
Programming in Scala - Lecture ThreeAngelo Corsaro
 
Fp in scala part 1
Fp in scala part 1Fp in scala part 1
Fp in scala part 1Hang Zhao
 
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...Andrew Phillips
 
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...Andrew Phillips
 
Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009Martin Odersky
 
Scala 3 Is Coming: Martin Odersky Shares What To Know
Scala 3 Is Coming: Martin Odersky Shares What To KnowScala 3 Is Coming: Martin Odersky Shares What To Know
Scala 3 Is Coming: Martin Odersky Shares What To KnowLightbend
 
Monad Transformers - Part 1
Monad Transformers - Part 1Monad Transformers - Part 1
Monad Transformers - Part 1Philip Schwarz
 
The Scala Programming Language
The Scala Programming LanguageThe Scala Programming Language
The Scala Programming Languageleague
 
Functional programming in kotlin with Arrow [Sunnytech 2018]
Functional programming in kotlin with Arrow [Sunnytech 2018]Functional programming in kotlin with Arrow [Sunnytech 2018]
Functional programming in kotlin with Arrow [Sunnytech 2018]Emmanuel Nhan
 
Introduction to matlab
Introduction to matlabIntroduction to matlab
Introduction to matlabvikrammutneja1
 
Scala Refactoring for Fun and Profit
Scala Refactoring for Fun and ProfitScala Refactoring for Fun and Profit
Scala Refactoring for Fun and ProfitTomer Gabel
 

Similar a Scala 3 enum for a terser Option Monad Algebraic Data Type (20)

The Great Scala Makeover
The Great Scala MakeoverThe Great Scala Makeover
The Great Scala Makeover
 
Monoids - Part 2 - with examples using Scalaz and Cats
Monoids - Part 2 - with examples using Scalaz and CatsMonoids - Part 2 - with examples using Scalaz and Cats
Monoids - Part 2 - with examples using Scalaz and Cats
 
Programming in Scala - Lecture Three
Programming in Scala - Lecture ThreeProgramming in Scala - Lecture Three
Programming in Scala - Lecture Three
 
Fp in scala part 1
Fp in scala part 1Fp in scala part 1
Fp in scala part 1
 
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...
BASE Meetup: "Analysing Scala Puzzlers: Essential and Accidental Complexity i...
 
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...
Scala Up North: "Analysing Scala Puzzlers: Essential and Accidental Complexit...
 
Imp_Points_Scala
Imp_Points_ScalaImp_Points_Scala
Imp_Points_Scala
 
Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009Scala Talk at FOSDEM 2009
Scala Talk at FOSDEM 2009
 
Scala 3 Is Coming: Martin Odersky Shares What To Know
Scala 3 Is Coming: Martin Odersky Shares What To KnowScala 3 Is Coming: Martin Odersky Shares What To Know
Scala 3 Is Coming: Martin Odersky Shares What To Know
 
Monad Transformers - Part 1
Monad Transformers - Part 1Monad Transformers - Part 1
Monad Transformers - Part 1
 
Go Course Day2
Go Course Day2Go Course Day2
Go Course Day2
 
Swift, swiftly
Swift, swiftlySwift, swiftly
Swift, swiftly
 
Scala in Places API
Scala in Places APIScala in Places API
Scala in Places API
 
Array
ArrayArray
Array
 
The Scala Programming Language
The Scala Programming LanguageThe Scala Programming Language
The Scala Programming Language
 
Functional programming in kotlin with Arrow [Sunnytech 2018]
Functional programming in kotlin with Arrow [Sunnytech 2018]Functional programming in kotlin with Arrow [Sunnytech 2018]
Functional programming in kotlin with Arrow [Sunnytech 2018]
 
Introduction to matlab
Introduction to matlabIntroduction to matlab
Introduction to matlab
 
Scala Refactoring for Fun and Profit
Scala Refactoring for Fun and ProfitScala Refactoring for Fun and Profit
Scala Refactoring for Fun and Profit
 
Scala for curious
Scala for curiousScala for curious
Scala for curious
 
Scala Paradigms
Scala ParadigmsScala Paradigms
Scala Paradigms
 

Más de Philip Schwarz

Direct Style Effect Systems - The Print[A] Example - A Comprehension Aid
Direct Style Effect Systems -The Print[A] Example- A Comprehension AidDirect Style Effect Systems -The Print[A] Example- A Comprehension Aid
Direct Style Effect Systems - The Print[A] Example - A Comprehension AidPhilip Schwarz
 
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesFolding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesPhilip Schwarz
 
Folding Cheat Sheet #3 - third in a series
Folding Cheat Sheet #3 - third in a seriesFolding Cheat Sheet #3 - third in a series
Folding Cheat Sheet #3 - third in a seriesPhilip Schwarz
 
Folding Cheat Sheet #2 - second in a series
Folding Cheat Sheet #2 - second in a seriesFolding Cheat Sheet #2 - second in a series
Folding Cheat Sheet #2 - second in a seriesPhilip Schwarz
 
Folding Cheat Sheet #1 - first in a series
Folding Cheat Sheet #1 - first in a seriesFolding Cheat Sheet #1 - first in a series
Folding Cheat Sheet #1 - first in a seriesPhilip Schwarz
 
Scala Left Fold Parallelisation - Three Approaches
Scala Left Fold Parallelisation- Three ApproachesScala Left Fold Parallelisation- Three Approaches
Scala Left Fold Parallelisation - Three ApproachesPhilip Schwarz
 
Tagless Final Encoding - Algebras and Interpreters and also Programs
Tagless Final Encoding - Algebras and Interpreters and also ProgramsTagless Final Encoding - Algebras and Interpreters and also Programs
Tagless Final Encoding - Algebras and Interpreters and also ProgramsPhilip Schwarz
 
Fusing Transformations of Strict Scala Collections with Views
Fusing Transformations of Strict Scala Collections with ViewsFusing Transformations of Strict Scala Collections with Views
Fusing Transformations of Strict Scala Collections with ViewsPhilip Schwarz
 
A sighting of traverse_ function in Practical FP in Scala
A sighting of traverse_ function in Practical FP in ScalaA sighting of traverse_ function in Practical FP in Scala
A sighting of traverse_ function in Practical FP in ScalaPhilip Schwarz
 
A sighting of traverseFilter and foldMap in Practical FP in Scala
A sighting of traverseFilter and foldMap in Practical FP in ScalaA sighting of traverseFilter and foldMap in Practical FP in Scala
A sighting of traverseFilter and foldMap in Practical FP in ScalaPhilip Schwarz
 
A sighting of sequence function in Practical FP in Scala
A sighting of sequence function in Practical FP in ScalaA sighting of sequence function in Practical FP in Scala
A sighting of sequence function in Practical FP in ScalaPhilip Schwarz
 
N-Queens Combinatorial Puzzle meets Cats
N-Queens Combinatorial Puzzle meets CatsN-Queens Combinatorial Puzzle meets Cats
N-Queens Combinatorial Puzzle meets CatsPhilip Schwarz
 
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...Kleisli composition, flatMap, join, map, unit - implementation and interrelat...
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...Philip Schwarz
 
The aggregate function - from sequential and parallel folds to parallel aggre...
The aggregate function - from sequential and parallel folds to parallel aggre...The aggregate function - from sequential and parallel folds to parallel aggre...
The aggregate function - from sequential and parallel folds to parallel aggre...Philip Schwarz
 
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
Nat, List and Option Monoids -from scratch -Combining and Folding -an exampleNat, List and Option Monoids -from scratch -Combining and Folding -an example
Nat, List and Option Monoids - from scratch - Combining and Folding - an examplePhilip Schwarz
 
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
Nat, List and Option Monoids -from scratch -Combining and Folding -an exampleNat, List and Option Monoids -from scratch -Combining and Folding -an example
Nat, List and Option Monoids - from scratch - Combining and Folding - an examplePhilip Schwarz
 
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...Philip Schwarz
 
Sum and Product Types - The Fruit Salad & Fruit Snack Example - From F# to Ha...
Sum and Product Types -The Fruit Salad & Fruit Snack Example - From F# to Ha...Sum and Product Types -The Fruit Salad & Fruit Snack Example - From F# to Ha...
Sum and Product Types - The Fruit Salad & Fruit Snack Example - From F# to Ha...Philip Schwarz
 
Algebraic Data Types for Data Oriented Programming - From Haskell and Scala t...
Algebraic Data Types forData Oriented Programming - From Haskell and Scala t...Algebraic Data Types forData Oriented Programming - From Haskell and Scala t...
Algebraic Data Types for Data Oriented Programming - From Haskell and Scala t...Philip Schwarz
 
Jordan Peterson - The pursuit of meaning and related ethical axioms
Jordan Peterson - The pursuit of meaning and related ethical axiomsJordan Peterson - The pursuit of meaning and related ethical axioms
Jordan Peterson - The pursuit of meaning and related ethical axiomsPhilip Schwarz
 

Más de Philip Schwarz (20)

Direct Style Effect Systems - The Print[A] Example - A Comprehension Aid
Direct Style Effect Systems -The Print[A] Example- A Comprehension AidDirect Style Effect Systems -The Print[A] Example- A Comprehension Aid
Direct Style Effect Systems - The Print[A] Example - A Comprehension Aid
 
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesFolding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a series
 
Folding Cheat Sheet #3 - third in a series
Folding Cheat Sheet #3 - third in a seriesFolding Cheat Sheet #3 - third in a series
Folding Cheat Sheet #3 - third in a series
 
Folding Cheat Sheet #2 - second in a series
Folding Cheat Sheet #2 - second in a seriesFolding Cheat Sheet #2 - second in a series
Folding Cheat Sheet #2 - second in a series
 
Folding Cheat Sheet #1 - first in a series
Folding Cheat Sheet #1 - first in a seriesFolding Cheat Sheet #1 - first in a series
Folding Cheat Sheet #1 - first in a series
 
Scala Left Fold Parallelisation - Three Approaches
Scala Left Fold Parallelisation- Three ApproachesScala Left Fold Parallelisation- Three Approaches
Scala Left Fold Parallelisation - Three Approaches
 
Tagless Final Encoding - Algebras and Interpreters and also Programs
Tagless Final Encoding - Algebras and Interpreters and also ProgramsTagless Final Encoding - Algebras and Interpreters and also Programs
Tagless Final Encoding - Algebras and Interpreters and also Programs
 
Fusing Transformations of Strict Scala Collections with Views
Fusing Transformations of Strict Scala Collections with ViewsFusing Transformations of Strict Scala Collections with Views
Fusing Transformations of Strict Scala Collections with Views
 
A sighting of traverse_ function in Practical FP in Scala
A sighting of traverse_ function in Practical FP in ScalaA sighting of traverse_ function in Practical FP in Scala
A sighting of traverse_ function in Practical FP in Scala
 
A sighting of traverseFilter and foldMap in Practical FP in Scala
A sighting of traverseFilter and foldMap in Practical FP in ScalaA sighting of traverseFilter and foldMap in Practical FP in Scala
A sighting of traverseFilter and foldMap in Practical FP in Scala
 
A sighting of sequence function in Practical FP in Scala
A sighting of sequence function in Practical FP in ScalaA sighting of sequence function in Practical FP in Scala
A sighting of sequence function in Practical FP in Scala
 
N-Queens Combinatorial Puzzle meets Cats
N-Queens Combinatorial Puzzle meets CatsN-Queens Combinatorial Puzzle meets Cats
N-Queens Combinatorial Puzzle meets Cats
 
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...Kleisli composition, flatMap, join, map, unit - implementation and interrelat...
Kleisli composition, flatMap, join, map, unit - implementation and interrelat...
 
The aggregate function - from sequential and parallel folds to parallel aggre...
The aggregate function - from sequential and parallel folds to parallel aggre...The aggregate function - from sequential and parallel folds to parallel aggre...
The aggregate function - from sequential and parallel folds to parallel aggre...
 
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
Nat, List and Option Monoids -from scratch -Combining and Folding -an exampleNat, List and Option Monoids -from scratch -Combining and Folding -an example
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
 
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
Nat, List and Option Monoids -from scratch -Combining and Folding -an exampleNat, List and Option Monoids -from scratch -Combining and Folding -an example
Nat, List and Option Monoids - from scratch - Combining and Folding - an example
 
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...
The Sieve of Eratosthenes - Part II - Genuine versus Unfaithful Sieve - Haske...
 
Sum and Product Types - The Fruit Salad & Fruit Snack Example - From F# to Ha...
Sum and Product Types -The Fruit Salad & Fruit Snack Example - From F# to Ha...Sum and Product Types -The Fruit Salad & Fruit Snack Example - From F# to Ha...
Sum and Product Types - The Fruit Salad & Fruit Snack Example - From F# to Ha...
 
Algebraic Data Types for Data Oriented Programming - From Haskell and Scala t...
Algebraic Data Types forData Oriented Programming - From Haskell and Scala t...Algebraic Data Types forData Oriented Programming - From Haskell and Scala t...
Algebraic Data Types for Data Oriented Programming - From Haskell and Scala t...
 
Jordan Peterson - The pursuit of meaning and related ethical axioms
Jordan Peterson - The pursuit of meaning and related ethical axiomsJordan Peterson - The pursuit of meaning and related ethical axioms
Jordan Peterson - The pursuit of meaning and related ethical axioms
 

Último

A Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxA Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxComplianceQuest1
 
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️Delhi Call girls
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerThousandEyes
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Modelsaagamshah0812
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Steffen Staab
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfkalichargn70th171
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...kellynguyen01
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionSolGuruz
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AIABDERRAOUF MEHENNI
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceCALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceanilsa9823
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...Health
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...panagenda
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsAndolasoft Inc
 

Último (20)

A Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxA Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docx
 
Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdfMicrosoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
 
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS LiveVip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
 
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Models
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
 
Diamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with PrecisionDiamond Application Development Crafting Solutions with Precision
Diamond Application Development Crafting Solutions with Precision
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
 
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICECHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female serviceCALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
CALL ON ➥8923113531 🔝Call Girls Badshah Nagar Lucknow best Female service
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.js
 

Scala 3 enum for a terser Option Monad Algebraic Data Type

  • 1. • Explore a terser definition of the Option Monad that uses a Scala 3 enum as an Algebraic Data Type. • In the process, have a tiny bit of fun with Scala 3 enums. • Get a refresher on the Functor and Monad laws. • See how easy it is to use Scala 3 extension methods, e.g. to add convenience methods and infix operators. @philip_schwarzslides by https://www.slideshare.net/pjschwarz enum for a terser Option Monad Algebraic Data Type..…
  • 2. We introduce a new type, Option. As we mentioned earlier, this type also exists in the Scala standard library, but we’re re-creating it here for pedagogical purposes: sealed trait Option[+A] case class Some[+A](get: A) extends Option[A] case object None extends Option[Nothing] Option is mandatory! Do not use null to denote that an optional value is absent. Let’s have a look at how Option is defined: sealed abstract class Option[+A] extends IterableOnce[A] final case class Some[+A](value: A) extends Option[A] case object None extends Option[Nothing] Since creating new data types is so cheap, and it is possible to work with them polymorphically, most functional languages define some notion of an optional value. In Haskell it is called Maybe, in Scala it is Option, … Regardless of the language, the structure of the data type is similar: data Maybe a = Nothing –- no value | Just a -- holds a value sealed abstract class Option[+A] // optional value case object None extends Option[Nothing] // no value case class Some[A](value: A) extends Option[A] // holds a value We have already encountered scalaz’s improvement over scala.Option, called Maybe. It is an improvement because it does not have any unsafe methods like Option.get, which can throw an exception, and is invariant. It is typically used to represent when a thing may be present or not without giving any extra context as to why it may be missing. sealed abstract class Maybe[A] { ... } object Maybe { final case class Empty[A]() extends Maybe[A] final case class Just[A](a: A) extends Maybe[A] Over the years we have all got very used to the definition of the Option monad’s Algebraic Data Type (ADT).
  • 3. With the arrival of Scala 3 however, the definition of the Option ADT becomes much terser thanks to the fact that it can be implemented using the new enum concept .
  • 4. OK, so this is, again, cool, now we have parity with Java, but we can actually go way further. enums can not only have value parameters, they also can have type parameters, like this. So you can have an enum Option with a covariant type parameter T and then two cases Some and None. So that of course gives you what people call an Algebraic Data Type, or ADT. Scala so far was lacking a simple way to write an ADT. What you had to do is essentially what the compiler would translate this to. A Tour of Scala 3 – by Martin Odersky Martin Odersky @odersky
  • 5. So the compiler would take this ADT that you have seen here and translate it into essentially this: And so far, if you wanted something like that, you would have written essentially the same thing. So a sealed abstract class or a sealed abstract trait, Option, with a case class as one case, and as the other case, here it is a val, but otherwise you could also use a case object. And that of course is completely workable, but it is kind of tedious. When Scala started, one of the main motivations, was to avoid pointless boilerplate. So that’s why case classes were invented, and a lot of other innovations that just made code more pleasant to write and more compact than Java code, the standard at the time. A Tour of Scala 3 – by Martin Odersky Martin Odersky @odersky
  • 6. enum Option[+A]: case Some(a: A) case None On the next slide we have a go at adding some essential methods to this terser enum-based Option ADT. @philip_schwarz
  • 7. enum Option[+A]: case Some(a: A) case None def map[B](f: A => B): Option[B] = this match case Some(a) => Some(f(a)) case None => None def flatMap[B](f: A => Option[B]): Option[B] = this match case Some(a) => f(a) case None => None def fold[B](ifEmpty: => B)(f: A => B) = this match case Some(a) => f(a) case None => ifEmpty def filter(p: A => Boolean): Option[A] = this match case Some(a) if p(a) => Some(a) case _ => None def withFilter(p: A => Boolean): Option[A] = filter(p) object Option : def pure[A](a: A): Option[A] = Some(a) def none: Option[Nothing] = None extension[A](a: A): def some: Option[A] = Some(a) Option is a monad, so we have given it a flatMap method and a pure method. In Scala the latter is not strictly needed, but we’ll make use of it later. Every monad is also a functor, and this is reflected in the fact that we have given Option a map method. We gave Option a fold method, to allow us to interpret/execute the Option effect, i.e. to escape from the Option container, or as John a De Goes puts it, to translate away from optionality by providing a default value. We want our Option to integrate with for comprehensions sufficiently well for our current purposes, so in addition to map and flatMap methods, we have given it a simplistic withFilter method that is just implemented in terms of filter, another pretty essential method. There are of course many many other methods that we would normally want to add to Option. The some and none methods are just there to provide the convenience of Cats-like syntax for lifting a pure value into an Option and for referring to the empty Option instance.
  • 8. Yes, the some method on the previous slide was implemented using the new Scala 3 feature of Extension Methods.
  • 9. On the next slide we do the following: • See our Option monad ADT again • Define a few enumerated types using use the Scala 3 enum feature. • Add a simple program showing the Option monad in action.
  • 10. enum Option[+A]: case Some(a: A) case None def map[B](f: A => B): Option[B] = this match case Some(a) => Some(f(a)) case None => None def flatMap[B](f: A => Option[B]): Option[B] = this match case Some(a) => f(a) case None => None def fold[B](zero: => B)(f: A => B) = this match case Some(a) => f(a) case None => zero def filter(p: A => Boolean): Option[A] = this match case Some(a) if p(a) => Some(a) case _ => None def withFilter(p: A => Boolean): Option[A] = filter(p) object Option : def pure[A](a: A): Option[A] = Some(a) def none: Option[Nothing] = None extension[A](a: A): def some: Option[A] = Some(a) enum Greeting(val language: Language): override def toString: String = s"${enumLabel} ${language.toPreposition}" case Welcome extends Greeting(English) case Willkommen extends Greeting(German) case Bienvenue extends Greeting(French) case Bienvenido extends Greeting(Spanish) case Benvenuto extends Greeting(Italian) enum Language(val toPreposition: String): case English extends Language("to") case German extends Language("nach") case French extends Language("à") case Spanish extends Language("a") case Italian extends Language("a") enum Planet: case Mercury, Venus, Earth, Mars, Jupiter, Saturn, Neptune, Uranus, Pluto, Scala3 case class Earthling(name: String, surname: String, languages: Language*) def greet(maybeGreeting: Option[Greeting], maybeEarthling: Option[Earthling], maybePlanet: Option[Planet]): Option[String] = for greeting <- maybeGreeting earthling <- maybeEarthling planet <- maybePlanet if earthling.languages contains greeting.language yield s"$greeting $planet ${earthling.name}!" @main def main = val maybeGreeting = greet( maybeGreeting = Some(Welcome), maybeEarthling = Some(Earthling("Fred", "Smith", English, Italian)), maybePlanet = Some(Scala3)) println(maybeGreeting.fold("Error: no greeting message") (msg => s"*** $msg ***")) *** Welcome to Scala3 Fred! ***
  • 11. def greet(maybeGreeting: Option[Greeting], maybeEarthling: Option[Earthling], maybePlanet: Option[Planet]): Option[String] = for greeting <- maybeGreeting earthling <- maybeEarthling planet <- maybePlanet if earthling.languages contains greeting.language yield s"$greeting $planet ${earthling.name}!" // Greeting Earthling Planet Greeting Message assert(greet(Some(Welcome), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == Some("Welcome to Scala3 Fred!")) assert(greet(Some(Benvenuto), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == Some("Benvenuto a Scala3 Fred!")) assert(greet(Some(Bienvenue), Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == None) assert(greet(None, Some(Earthling("Fred", "Smith", English, Italian)), Some(Scala3)) == None) assert(greet(Some(Welcome), None, Some(Scala3)) == None) assert(greet(Some(Welcome), Some(Earthling("Fred", "Smith", English, Italian)), None) == None) assert(greet(Welcome.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == ("Welcome to Scala3 Fred!").some) assert(greet(Benvenuto.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == ("Benvenuto a Scala3 Fred!").some) assert(greet(Bienvenue.some, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == none) assert(greet(none, Earthling("Fred", "Smith", English, Italian).some, Scala3.some) == none) assert(greet(Welcome.some, none, Scala3.some) == none) assert(greet(Welcome.some, Earthling("Fred", "Smith", English, Italian).some, none) == none) Same again, but this time using the some and none convenience methods. Below are some tests for our simple program. @philip_schwarz
  • 12. val stringToInt: String => Option[Int] = s => Try { s.toInt }.fold(_ => None, Some(_)) assert( stringToInt("123") == Some(123) ) assert( stringToInt("1x3") == None ) assert( intToChars(123) == Some(List('1', '2', '3'))) assert( intToChars(0) == Some(List('0'))) assert( intToChars(-10) == None) assert(charsToInt(List('1', '2', '3')) == Some(123) ) assert(charsToInt(List('1', 'x', '3')) == None ) val intToChars: Int => Option[List[Char]] = n => if n < 0 then None else Some(n.toString.toArray.toList) val charsToInt: Seq[Char] => Option[Int] = chars => Try { chars.foldLeft(0){ (n,char) => 10 * n + char.toString.toInt } }.fold(_ => None, Some(_)) def doublePalindrome(s: String): Option[String] = for n <- stringToInt(s) chars <- intToChars(2 * n) palindrome <- charsToInt(chars ++ chars.reverse) yield palindrome.toString assert( doublePalindrome("123") == Some("246642") ) assert( doublePalindrome("1x3") == None ) The remaining slides provide us with a refresher of the functor and monad laws. To do so, they use two examples of ordinary functions and three examples of Kleisli arrows, i.e. functions whose signature is of the form A => F[B], for some monad F, which in our case is the Option monad. The example functions are defined below, together with a function that uses them. While the functions are bit contrived, they do the job. The reason why the Kleisli arrows are a bit more complex than would normally be expected is that since in this slide deck we are defining our own simple Option monad, we are not taking shortcuts that involve the standard Scala Option, e.g. converting a String to an Int using the toIntOption function available on String. val double: Int => Int = n => 2 * n val square: Int => Int = n => n * n
  • 13. Since every monad is also a functor, the next slide is a reminder of the functor laws. We also define a Scala 3 extension method to provide syntax for the infix operator for function composition.
  • 14. // FUNCTOR LAWS // identity law: ma map identity = identity(ma) assert( (f(a) map identity) == identity(f(a)) ) assert( (a.some map identity) == identity(a.some) ) assert( (none map identity) == identity(none) ) // composition law: ma map (g ∘ h) == ma map h map g assert( (f(a) map (g ∘ h)) == (f(a) map h map g) ) assert( (3.some map (g ∘ h)) == (3.some map h map g) ) assert( (none map (g ∘ h)) == (none map h map g) ) val f = stringToInt val g = double val h = square val a = "123" // plain function composition extension[A,B,C](f: B => C) def ∘ (g: A => B): A => C = a => f(g(a)) def identity[A](x: A): A = x enum Option[+A]: case Some(a: A) case None def map[B](f: A => B): Option[B] = this match case Some(a) => Some(f(a)) case None => None ... object Option : def pure[A](a: A): Option[A] = Some(a) def none: Option[Nothing] = None extension[A](a: A): def some: Option[A] = Some(a) assert( stringToInt("123") == Some(123) ) assert( stringToInt("1x3") == None ) val double: Int => Int = n => 2 * n val square: Int => Int = n => n * n
  • 15. // FUNCTOR LAWS // identity law: ma map identity = identity(ma) assert( (f(a) map identity) == identity(f(a)) ) assert( (a.some map identity) == identity(a.some) ) assert( (none map identity) == identity(none) ) // composition law: ma map (g ∘ h) == ma map h map g assert( (f(a) map (g ∘ h)) == (f(a) map h map g) ) assert( (3.some map (g ∘ h)) == (3.some map h map g) ) assert( (none map (g ∘ h)) == (none map h map g) ) val f = stringToInt val g = double val h = square val a = "123" // plain function composition extension[A,B,C](f: B => C) def ∘ (g: A => B): A => C = a => f(g(a)) def identity[A](x: A): A = x enum Option[+A]: case Some(a: A) case None def map[B](f: A => B): Option[B] = this match case Some(a) => Some(f(a)) case None => None ... object Option : def pure[A](a: A): Option[A] = Some(a) def none: Option[Nothing] = None extension[A](a: A): def some: Option[A] = Some(a) assert( stringToInt("123") == Some(123) ) assert( stringToInt("1x3") == None ) val double: Int => Int = n => 2 * n val square: Int => Int = n => n * n
  • 16. @philip_schwarz While the functor Identity Law is very simple, the fact that it can be formulated in slightly different ways can sometimes be a brief source of puzzlement when recalling the law. On the next slide I have a go at recapping three different ways of formulating the law.
  • 17. F(idX) = idF(X) fmap id = id fmapMaybe ida x = idMaybe a x Option(idX) = idOption(X) x map (a => a) = x mapOption(idX) = idOption(X) x mapOption (idX) = idOption(X)(x) fmapF ida = idF a fmapMaybe ida = idMaybe a λ> :type fmap fmap :: Functor f => (a -> b) -> f a -> f b λ> inc x = x + 1 λ> fmap inc (Just 3) Just 4 λ> fmap inc Nothing Nothing λ> :type id id :: a -> a λ> id 3 3 λ> id (Just 3) Just 3 λ> fmap id Just 3 == id Just 3 True λ> fmap id Nothing == id Nothing True scala> :type Option(3).map (Int => Any) => Option[Any] scala> val inc: Int => Int = n => n + 1 scala> Some(3) map inc val res1: Option[Int] = Some(4) scala> None map inc val res2: Option[Int] = None scala> :type identity Any => Any scala> identity(3) val res3: Int = 3 scala> identity(Some(3)) val res4: Some[Int] = Some(3) scala> (Some(3) map identity) == identity(Some(3)) val res10: Boolean = true scala> (None map identity) == identity(None) val res11: Boolean = true Functor Option Maybe x map identity = identity(x) fmap id x = id x Category TheoryScala Haskell Some, None Just, Nothing Functor Identity Law
  • 18. The last two slides of this deck remind us of the monad laws. They also make use of Scala 3 extension methods, this time to provide syntax for the infix operators for flatMap and Kleisli composition.
  • 19. // MONAD LAWS // left identity law: pure(a) flatMap f == f(a) assert( (pure(a) flatMap f) == f(a) ) // right identity law: ma flatMap pure == ma assert( (f(a) flatMap pure) == f(a) ) assert( (a.some flatMap pure) == a.some ) assert( (none flatMap pure) == none ) // associativity law: ma flatMap f flatMap g = ma flatMap (a => f(a) flatMap g) assert( ((f(a) flatMap g) flatMap h) == (f(a) flatMap (x => g(x) flatMap h)) ) assert( ((3.some flatMap g) flatMap h) == (3.some flatMap (x => g(x) flatMap h)) ) assert( ((none flatMap g) flatMap h) == (none flatMap (x => g(x) flatMap h)) ) enum Option[+A]: case Some(a: A) case None ... def flatMap[B](f: A => Option[B]): Option[B] = this match case Some(a) => f(a) case None => None ... object Option : def pure[A](a: A): Option[A] = Some(a) def none: Option[Nothing] = None def id[A](oa: Option[A]): Option[A] = oa extension[A](a: A): def some: Option[A] = Some(a) val f = stringToInt val g = intToChars val h = charsToInt val a = "123” assert( stringToInt("123") == Some(123) ) assert( stringToInt("1x3") == None ) assert( intToChars(123) == Some(List('1', '2', '3'))) assert( intToChars(0) == Some(List('0'))) assert( intToChars(-10) == None) assert(charsToInt(List('1', '2', '3')) == Some(123) ) assert(charsToInt(List('1', 'x', '3')) == None )
  • 20. The monad laws again, but this time using a Haskell-style bind operator as an alias for flatMap. And here are the monad laws expressed in terms of Kleisli composition (the fish operator).
  • 21. If you are new to functor laws and/or monad laws you might want to take a look at some of the following https://www2.slideshare.net/pjschwarz/functor-laws https://www2.slideshare.net/pjschwarz/monad-laws-must-be-checked-107011209 https://www2.slideshare.net/pjschwarz/rob-norrisfunctionalprogrammingwitheffects
  • 22. That’s all. I hope you found it useful. @philip_schwarz