Key Terminology

Read this entire walkthrough.

Getting started with fp-ts: EqDEV Community

Type / Category

A type is a mathematical concept referring to a category, in lay-speak. The more formal idea of a category is better defined as:

• Consistent groupings of objects

• Certain transformations between those groupings, known as morphisms

An object may also be a morhphism, this is where Functors come in.

Function

Denoted as f(a) Defines a mapping between types, taking the form:

f: a -> b

Where a is the input type and b is the output type.

Algebra

An algebra is a family of functions with the signature f: a -> a for a given category a.

Type Constructor

A type constructor is an n-ary type operator taking as argument zero or more types, and returning another type. It has the type of signature:

a -> F<a>

Often used to model side-effects in a program. Examples include:

List<a> Option<a> Task<a>

Catamorphism

A catamorphism is a generalised morphism concept that performs an operation known as fold or reduce.

The name comes from the Greek 'κατα-' meaning "downward or according to". A useful mnemonic is to think of a catastrophe destroying something.

Catamorphisms - HaskellWiki

Functor

A type constructor is classed as a Functor if the lift operation can be defined for it. To avoid further confusion let it be clear that lift, map and fmap can be conceptually considered equivalent.

Say we have:

f: a -> F<b>

g: b -> c

How can we compose f and g together? lifting is the process of taking b -> c and creating F<b> -> F<c>.

Which in turn lets us compose a -> F<b> and F<b> -> F<c> trivially as a -> F<b> -> F<c> and ultimately a -> F<c>.

A more complete way to define a Functor is that it is made up of two aspects:

• A type constructor F: a mapping between objects that associates to each object X in a an object in b

• A function lift: a mapping between morphisms that associates to each morphism in c a morphism in d

Examples:

let lift (g: b -> c) (fb: List<b>) = fb |> List.map g

function lift<B, C>(g: (b: B) => C): (fb: Array<B>) => Array<C> {
  return fb => fb.map(g)
}

function lift<B, C>(g: (b: B) => C): (fb: Option<B>) => Option<C> {
  return fb => (isNone(fb) ? none : some(g(fb.value)))
}

function lift<B, C>(g: (b: B) => C): (fb: Task<B>) => Task<C> {
  return fb => () => fb().then(g)
}

Getting started with fp-ts: FunctorDEV Community

Endofunctors

An endofunctor is a functor mapping to and from the same category, F: C -> C.

The simplest example of an endofunctor is id which has the signature a -> a. We can define the identity endofunctor as:

module Identity =
    // ('a -> 'b) -> Identity<'a> -> Identity<'b>
    let map f (Identity x) = Identity (f x)

Similarly, the Maybe endofunctor has the form:

instance Functor Maybe where
  fmap f Nothing = Nothing
  fmap f (Just x) = Just (f x)

If unclear, the defining property that makes a functor an endofunctor above is that fmap always preserves the category, which is not necessarily true for a functor.

The Identity functorploeh

F-Algebra

Building on the base idea of an algebra, an F-Algebra is composed of three things:

• An endofunctor F

• An object a that is "inside" the endofunctor as the carried type

• A morphism of the form F<a> -> a, often called the evaluation function or the structure map

Once again, Maybe is an example of an F-Algebra.

data MaybeF a c = NothingF | JustF a deriving (Show, Eq, Read)
 
instance Functor (MaybeF a) where
  fmap _  NothingF = NothingF
  fmap _ (JustF x) = JustF x

Maybe catamorphismploeh

Semigroup

A semigroup is a pair (A, *) in which A is a non-empty set and * is a binary associative operation on A, i.e. a function that takes two elements of A as input and returns an element of A as output.

Effectively, this means that the concat morphism can be defined.

interface Semigroup<A> {
  concat: (x: A, y: A) => A
}

const semigroupProduct: Semigroup<number> = {
  concat: (x, y) => x * y
}

const semigroupSum: Semigroup<number> = {
  concat: (x, y) => x + y
}

const semigroupString: Semigroup<string> = {
  concat: (x, y) => x + y
}

Applicative Functors

A Functor is classed as Applicative if the apply morphism can be defined for it, these are also simply known as Applicatives for short. In practical terms this property allows us to handle n-ary Functors rather than just unary.

apply as an operation on the functor instance F is able to unpack the value F<(c: C) => D> to a function (fc: F<C>) => F<D>.

Examples

F = Array

import { flatten } from 'fp-ts/lib/Array'

const applicativeArray = {
  map: <A, B>(fa: Array<A>, f: (a: A) => B): Array<B> => fa.map(f),
  of: <A>(a: A): Array<A> => [a],
  ap: <A, B>(fab: Array<(a: A) => B>, fa: Array<A>): Array<B> =>
    flatten(fab.map(f => fa.map(f))) // flatten prevents [['a']] style output
}

F = Option

import { Option, some, none, isNone } from 'fp-ts/lib/Option'

const applicativeOption = {
  map: <A, B>(fa: Option<A>, f: (a: A) => B): Option<B> =>
    isNone(fa) ? none : some(f(fa.value)),
  of: <A>(a: A): Option<A> => some(a),
  ap: <A, B>(fab: Option<(a: A) => B>, fa: Option<A>): Option<B> =>
    isNone(fab) ? none : applicativeOption.map(fa, fab.value)
}

F = Task

import { Task } from 'fp-ts/lib/Task'

const applicativeTask = {
  map: <A, B>(fa: Task<A>, f: (a: A) => B): Task<B> => () => fa().then(f),
  of: <A>(a: A): Task<A> => () => Promise.resolve(a),
  ap: <A, B>(fab: Task<(a: A) => B>, fa: Task<A>): Task<B> => () =>
    Promise.all([fab(), fa()]).then(([f, a]) => f(a))
}

Getting started with fp-ts: ApplicativeDEV Community

Monoid

A Monoid is any Semigroup that happens to have a special value which is "neutral" with respect to concat. Do note, not all Semigroups are Monoids.

import { Semigroup } from 'fp-ts/lib/Semigroup'

interface Monoid<A> extends Semigroup<A> {
  readonly empty: A
}

The following laws must hold

• Right identity: concat(x, empty) = x, for all x in A

• Left identity: concat(empty, x) = x, for all x in A

/** number `Monoid` under addition */
const monoidSum: Monoid<number> = {
  concat: (x, y) => x + y,
  empty: 0
}

/** number `Monoid` under multiplication */
const monoidProduct: Monoid<number> = {
  concat: (x, y) => x * y,
  empty: 1
}

const monoidString: Monoid<string> = {
  concat: (x, y) => x + y,
  empty: ''
}

/** boolean monoid under conjunction */
const monoidAll: Monoid<boolean> = {
  concat: (x, y) => x && y,
  empty: true
}

/** boolean monoid under disjunction */
const monoidAny: Monoid<boolean> = {
  concat: (x, y) => x || y,
  empty: false
}

Non-Monoidal Semigroup

A trivial example of a semigroup for which empty cannot be defined to satisfy the right and left identity laws.

const semigroupSpace: Semigroup<string> = {
  concat: (x, y) => x + ' ' + y
}

Getting started with fp-ts: MonoidDEV Community

Monad

A Monad is simply a Monoid in the category of Endofunctors 🙃.

What this practically means is that we can define the operations:

• of: a -> M<a>

• map: M<a> -> M<b>

• get: M<a> -> a

• concat: M<a> -> M<a> -> M<a>

• flatten: M<M<a>> -> M<a>

• flatMap: (a -> M<b>) -> (M<a> -> M<b>)

Pending questions to directly address:

• how does filter fit in?

• define transducers

• draw a diagram of related terms

• how does a catamorphism interact with the definitions of semigroup, monoid and monad?

• what is the common set of useful morphisms?

  • map

  • get

  • concat

  • bind / chain / of(?)

  • apply

  • fold

  • unfold