Functions, Types, Programs and Effects

FUNCTIONS, TYPES,
PROGRAMS AND EFFECTS

What does this do?
(maybeInt1 |@| maybeInt2) { _ > _ } | false

scalaz.SemiGroup
scalaz.Monoid
scalaz.PlusEmpty

scalaz.Functor
scalaz.Applicative
scalaz.Monad

scalaz.ApplicativePlus
scalaz.MonadPlus

Does SI-2712 ring a bell?
scalaz.Unapply[TC[_[_]], MA]
traverseU

EitherT[F[_], A, B]
OptionT[F[_], A]

Do you use scalaz or cats for your day job?

FUNCTIONS, TYPES, PROGRAMS AND EFFECTS
Strict separation of safe and unsafe
Safe: Functions, Types, creating Programs
Unsafe: Effects, running Programs

WRITING FUNCTIONAL SCALA
1. Write functions, which return values
2. Choose effects (or write your own)
3. Construct a program that composes values into effects
4. Run the program (in an 'App' in the main method)
(Not necessarily in that order)

▸ You can possibly have programs of programs
▸ A program is very often defined in a for comprehension

A hypothetical example.
val program = for {
client <- server.connect(details)
Exchange(src, snk) = client.exchange
_ <- snk.sendRequest(request)
in = src.pipe(text.utf8Decode)
.to(io.stdOutLines)
} yield ()
program.run
Define first, run later.

BUT FIRST: SOMETHING
ABOUT INFORMATION LOSS

QUIZKEEP IN MIND: FUNCTIONS, TYPES,
PROGRAMS, EFFECTS

Anything 'wrong' with these methods / functions?
def getUser(username: Username): Future[User]
def createUser(details: UserDetails): Future[User]
def getPrimaryAccount(user: User): Future[Account]

Anything 'wrong' with this?
def getUser(username: Username): Future[Option[User]]
def getAccounts(user: User): Future[List[Account]]
def approved(user: User, accounts: List[Account]): Future[Boolean]

DATA LOSS
Boolean blindness
Functions return values, discarding them constrains the Program 1
1
Think of the information you need later on in a for comprehension

What is 'wrong' with this?
sealed trait Error
case object UserNotFound extends Error
case object UserNameNotFound extends Error
case object AccountNotFound extends Error
def getUser(username: Username): Future[Either[Error, User]]
def getAccounts(user: User): Future[Either[Error, Account]]

scalaz Disjunction (left or right)
val res: String / Int = /-(5)
val res1: String / Int = 5.right
val moreVerbose: String / Int = 5.right[String]
val res2: String / Int = "Some error".left
val friendlier = res2.leftMap(error => s"$error has occured, we apologize.")
val res3 = res1.map(five => five * 2) // /-(10)
Map over the right

From Throwable to /
/.fromTryCatchThrowable[String, Exception] {
getDangerousString()
} // returns a Exception / String
/.fromTryCatchThrowable[String, Exception] {
getDangerousString()
}.leftMap(e=> MyError(e)) // returns a MyError / String

From A / B to X
val res: String / Int = "Error!".left
val res1 = res.fold(left=> 0, r => r)
val res2 = res.fold(left=> 0, identity) // this is the same
Why should you not use this?

Combining /
case class Error(in: Int, reason: String)
def even(in: Int): Error / Int =
if(in % 2 == 0) in.right
else Error(in, "not even").left
def divByThree(in: Int): Error / Int =
if(in % 3 == 0) in.right
else Error(in, "not div 3").left
def evenAndByThree(in: Int) =
for {
evenNr <- even(in)
byThree <- divByThree(evenNr)
} yield byThree
println(evenAndByThree(12)) // /-(12)
println(evenAndByThree(3)) // -/-(3, "not even")
println(evenAndByThree(4)) // -/-(4, "not div 3")

def evenAndByThree(in: Int) =
for {
evenNr <- even(in)
byThree <- divByThree(evenNr)
} yield byThree
No loss of information (why the first error occurred).

Given
def getUser(username: Username): Future[Error / User]]
def getAccounts(user: User): Future[Error / List[Account]]
Does this compile?
val result = for {
user <- getUser(name)
accounts <- getAccounts(user)
} yield accounts

Combining values
Monoid - collecting / combining values into one value
//simplified / pseudo
val append: (F,F) => F
val zero: F
//actual
def append(f1: F, f2: => F): F
def zero: F

COMBINING EFFECTS
Monad - collecting / combining effects 2
def point[A](a: => A): F[A] // Creates an 'effects collector'
def bind[A, B](fa: F[A])(f: A => F[B]): F[B] // adds an effect
def map[A,B](fa: F[A])(f: A => B):F[B] // transforms input for next effect
Can only combine for same type of F.2
2
The Monad is a monoid in the category of endofunctors joke

In scalaz, flatMap is defined as:
def flatMap[B](f: A => F[B]) = F.bind(self)(f)
flatMap ~= bind

Monads are great, but in general NOT composable.
Monad Transformers
Effect systems (i.e. Eff from eff-cats)
In common, a Type that combines N Monad types

Monad Transformer EitherT
val res = for {
user <- EitherT(getUser("bla"))
accounts <- EitherT(getAccounts(user))
} yield accounts // returns EitherT[Future, Error, List[Account]]
res.run // Future[Error / List[Account]]
Scalaz provides Future Monad instance in scalaz.std.scalaFuture

Construct the Program
val res = for {
user <- EitherT(getUser("bla"))
accounts <- EitherT(getAccounts(user))
} yield accounts
Run the Program
res.run

Sometimes... a Monad Wrapper is a good enough Program

WRITE YOUR OWN MONAD
WRAPPER 3
3
specific monad transformer?

WRITE YOUR OWN MONAD WRAPPER
Topics (Kafka library)
Combine Future and /
Covariant +A/+B
Know why a Kafka operation failed in a Program

Why not EitherT?
final case class EitherT[F[_], A, B](run: F[A / B])
Invariant in A,B

Covariant Error type
sealed trait TopicsError
sealed trait FindTopicError extends TopicsError
sealed trait SelectTopicError extends TopicsError
sealed trait DeleteTopicError extends TopicsError

Example program
val program: Topics[TopicsError, Chunk[String, String]] = for {
partition ← Topics.partitioned[String, String](topicDef, partitionId)
info ← partition.write(record)
chunk ← partition.read(info.offset, info.offset)
} yield chunk
// ... somewhere later
program.run(broker, executionContext)

Minor detour (type lambda)
Monad[{ type λ[α] = Topics[E, α] })#λ]
~=
type MyMonad[T] = Monad[Topics[E, T]]
only inline.

Roll your own Monad instance (Scalaz)
object Topics {
implicit def topicsMonad[E] = new Monad[({ type λ[α] = Topics[E, α] })#λ] {
def point[T](value: T): Topics[E, T] = Topics.point(value)
def bind[T, U](topics: Topics[E, T])(f: T Topics[E, U]): Topics[E, U] = topics.flatMap(f)
}
}
delegate to point and flatMap

Roll your own Monad
case class Topics[+E, +T](run: (TopicBroker, ExecutionContext) Future[E / T]) {
// more to follow

Roll your own Monad
def map[C](f: T C): Topics[E, C] =
Topics((broker, ec) run(broker, ec).map(_.map(f))(ec))
def flatMap[E1 >: E, C](f: T Topics[E1, C]): Topics[E1, C] =
Topics { (broker, ec)
run(broker, ec).flatMap(
_.fold(err Future.successful(-/(err)), res f(res).run(broker, ec))
)(ec)
}
}

def map[C](f: T C): Topics[E, C] =
zoom in
zoom in
run(broker, ec).map(_.map(f))

Topics { (broker, ec)
)(ec)
}
zoom in
)(ec)
zoom in
fold(err Future.successful(-/(err)), res f(res).run(broker, ec))

Convenience methods
object Topics {
def run[E, T](broker: TopicBroker, action: Topics[E, T])(implicit ec: ExecutionContext): Future[E / T] = action.run(broker, ec)
def point[T](value: T): Topics[Nothing, T] = Topics[Nothing, T]((broker, ec) Future.successful(value.right))
def future[T](action: Future[T]): Topics[Nothing, T] = Topics((broker, ec) action.map(_.right)(ec))
def futureF[T](action: ExecutionContext Future[T]): Topics[Nothing, T] = Topics((broker, ec) action(ec).map(_.right)(ec))
def either[E, T](either: E / T): Topics[E, T] = Topics((_, _) Future.successful(either))
def futureEither[E, T](action: Future[E / T]): Topics[E, T] = Topics((_, _) action)
def futureEitherF[E, T](action: ExecutionContext Future[E / T]): Topics[E, T] = Topics((_, ec) action(ec))
// ... more code
}

import scalaz.scalacheck.ScalazProperties.monad
class MonadLawsSpec extends Spec {
def is = s2"""obey the monad laws $laws"""
def laws = {
implicit val b = broker
monad.laws[({ type l[a] = Topics[Int, a] })#l]
}
}

Another Program example
opt-parse-applicative
"net.bmjames" %% "scala-optparse-applicative" % "0.3"

case class Config(inputFile: Option[File], outputFile: Option[File])
def main(args: Array[String]): Unit = {
val config = parseArgs(args)
// ...
}

val inputFile = optional(opt[File](
ensure[File](readStr.map(str new File(str)), "INPUT_FILE must be an existing file", _.isFile),
long("input-file"),
metavar("INPUT_FILE"),
short('f'),
help("input file to read from")
))
val outputFile = optional(opt[File](
readStr.map(str new File(str)),
long("output-file"),
metavar("OUTPUT_FILE"),
short('o'),
help("output file to write to")
))

def parseArgs(args: Array[String]): Config = {
val inputFile = optional(opt[File]( // ... omitted
val outputFile = optional(opt[File]( // ... omitted
val parser = (input |@| inputFile)(Config.apply(_, _))
execParser(args, "copy", info(parser <*> helper,
header("The awesome copy utility.")
))
}

Define the program
val parser = (input |@| inputFile)(Config.apply(_, _))
Execute the program
execParser(args, "copy", info(parser <*> helper,
header("The awesome copy utility.")
))

Scalaz has virtually no docs )-:

Scalaz has really cool stuff (-:

On a lazy Sunday..
trait MonadPlus[F[_]] extends Monad[F] with ApplicativePlus[F] { self =>
//...
/** Generalized version of Haskell's `partitionEithers` */
def separate[G[_, _], A, B](value: F[G[A, B]])(implicit G: Bifoldable[G]): (F[A], F[B]) = {
val lefts = bind(value)((aa) => G.leftFoldable.foldMap(aa)(a => point(a))(monoid[A]))
val rights = bind(value)((bb) => G.rightFoldable.foldMap(bb)(b => point(b))(monoid[B]))
(lefts, rights)
}
//...
final class MonadPlusOps[F[_],A] private[syntax](val self: F[A])(implicit val F: MonadPlus[F]) extends Ops[F[A]] {
final def separate[G[_, _], B, C](implicit ev: A === G[B, C], G: Bifoldable[G]): (F[B], F[C]) =
F.separate(ev.subst(self))
//...
You read some code..

But, separate is very useful.
def separate[G[_, _], A, B](value: F[G[A, B]])(implicit G: Bifoldable[G]): (F[A], F[B])
Remove everything, keep args and return value
(value: F[G[A, B]]): (F[A], F[B])

(value: F[G[A, B]]): (F[A], F[B])
Remove remaining 'syntax'
F[G[A, B]] => (F[A], F[B])

Lets substitute F, G, A and B to something we know
F[G[A, B]] => (F[A], F[B])
F = List
G[A,B] = Error / Result
4
4
/ uses infix type notation, same as /[Error,Result]

List[Error / Result] => (List[Error], List[Result])
It's a function to separate the errors from the results!

There are many of these.
How do you find a concrete function if they are defined in the abstract?

DIG
Remove all syntax until you are left with a function
Then find which implicits / type classes are needed for the function.
Scalaz requires you to know how the typeclasses are organized

cats project has more docs
An introduction to cats
http://typelevel.org/cats/
Advanced Scala with Cats book 5
http://underscore.io/blog
5
http://underscore.io/books/advanced-scala/

Functional Programming in Scala (the red book) 6
6
https://www.manning.com/books/functional-programming-in-scala

http://typelevel.org/blog (Some articles are really advanced)

▸ Write functions
▸ Choose effects (or write your own)
▸ Construct a program that composes the functions and effects
▸ Run the program (in an 'App' in the main method)

RETURN VALUES
Use data types like A / B that do not lose information about what
happened
Boolean blindness
'Option flatMap' blindness?

PROGRAMS
Choose a reasonable architecture to construct your Programs
Monad Wrappers
Monad Transformers
Effect Systems

Functions, Types, Programs and Effects

Functions, Types, Programs and Effects

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