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Category theory for beginners

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Explains the basic concepts of Category Theory, useful terminology to help understand the literature, and why it's so relevant to software engineering.

Publié dans : Ingénierie
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Category theory for beginners

  1. 1. Category Theory for beginners Melbourne Scala User Group Feb 2015 @KenScambler A B C
  2. 2. Abstract maths… for us? Dizzyingly abstract branch of maths “Abstract nonsense”? Programming = maths Programming = abstraction Really useful to programming!
  3. 3. The plan Basic Category Theory concepts New vocabulary (helpful for further reading) How it relates to programming Category Theory as seen by maths versus FP
  4. 4. A bit of background 1940s Eilenberg, Mac Lane invent Category Theory 1958 Monads discovered by Godement In programming: 1990 Moggi, Wadler apply monads to programming 2006 “Applicative Programming with Effects” McBride & Paterson 2006 “Essence of the Iterator Pattern” Gibbons & Oliveira
  5. 5. I. Categories
  6. 6. Category Objects
  7. 7. Category Objects Arrows or morphisms
  8. 8. Category Objects Arrows Domain f dom(f)
  9. 9. Category Objects Arrows Domain/Codomain f cod(f) dom(f)
  10. 10. Category Objects Arrows Domain/Codomain dom(g) cod(g) g
  11. 11. Category Objects Arrows Domain/Codomain
  12. 12. Category Objects Arrows Domain/Codomain Composition f
  13. 13. Category Objects Arrows Domain/Codomain Composition f g
  14. 14. Category Objects Arrows Domain/Codomain Composition f g g ∘ f
  15. 15. Category Objects Arrows Domain/Codomain Composition f
  16. 16. Category Objects Arrows Domain/Codomain Composition f h
  17. 17. Category Objects Arrows Domain/Codomain Composition f h h ∘ f
  18. 18. Category Objects Arrows Domain/Codomain Composition Identity
  19. 19. Category Compose ∘ : (B  C)  (A  B)  (A  C) Identity id : A  A
  20. 20. Category Laws Associative Law (f ∘ g) ∘ h = f ∘ (g ∘ h ) Identity Laws f ∘ id = id ∘ f = f
  21. 21. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  22. 22. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  23. 23. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  24. 24. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  25. 25. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  26. 26. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  27. 27. Associative law (f ∘ g) ∘ h = f ∘ (g ∘ h ) f g h (g ∘ h) (f ∘ g)
  28. 28. Identity laws f ∘ id = id ∘ f = f f id id
  29. 29. Identity laws f ∘ id = id ∘ f = f f id id
  30. 30. Identity laws f ∘ id = id ∘ f = f f id id
  31. 31. Identity laws f ∘ id = id ∘ f = f f id id
  32. 32. Examples Infinite categories Finite categories Objects can represent anything Arrows can represent anything As long as we have composition and identity!
  33. 33. Sets & functions Person String Integer bestFriend length name age +1
  34. 34. Sets & functions Infinite arrows from composition +1∘ length ∘ name bestFriend ∘ bestFriend bestFriend ∘ bestFriend ∘ bestFriend +1∘ age∘ bestFriend
  35. 35. Sets & functions Objects Arrows Composition Identity
  36. 36. Sets & functions Objects = sets (or types) Arrows = functions Composition = function composition Identity = identity function
  37. 37. Zero
  38. 38. One
  39. 39. Two
  40. 40. Three
  41. 41. Class hierarchy IFruit IBanana AbstractBanana BananaImpl MockBanana Tool Spanner
  42. 42. Class hierarchy Objects Arrows Composition Identity
  43. 43. Class hierarchy Objects = classes Arrows = “extends” Composition = “extends” is transitive Identity = trivial
  44. 44. Class hierarchy Partially ordered sets (posets) Objects = elements in the set Arrows = ordering relation ≤ Composition = ≤ is transitive Identity = trivial
  45. 45. World Wide Web www.naaawcats.com No dogs allowed! www.robodogs.com See here for more robots www.coolrobots.com BUY NOW!!!!
  46. 46. World Wide Web Objects = webpages Arrows = hyperlinks Composition = Links don’t compose Identity
  47. 47. World Wide Web Graphs Objects = nodes Arrows = edges Composition = Edges don’t compose Identity
  48. 48. “Free Category” from graphs! Objects = nodes Arrows = paths (0 to many edges) Composition = aligning paths end to end Identity = you’re already there
  49. 49. Categories in code trait Category[Arrow[_,_]] { def compose[A,B,C]( c: Arrow[B,C], d: Arrow[A,B]): Arrow[A,C] def id[A]: Arrow[A,A] }
  50. 50. Category of Types & Functions object FnCat extends Category[Function1] { def compose[A,B,C]( c: B => C, d: A => B): A => C = { a => c(d(a)) } def id[A]: A => A = (a => a) }
  51. 51. Category of Garden Hoses sealed trait Hose[In, Out] { def leaks: Int def kinked: Boolean def >>[A](in: Hose[A, In]): Hose[A, Out] def <<[A](out: Hose[Out, A]): Hose[In, A] }
  52. 52. Category of Garden Hoses [live code example]
  53. 53. Categories embody the principle of strongly-typed composability
  54. 54. II. Functors
  55. 55. Functors Functors map between categories Objects  objects Arrows  arrows Preserves composition & identity
  56. 56. Functor laws Composition Law F(g ∘ f) = F(g) ∘ F(f) Identity Law F(idA) = idF(A)
  57. 57. C F DCategory Category Functor
  58. 58. C F DCategory Category Functor CatCategory of categories
  59. 59. C F DCategory Category Functor CatCategory of categories Objects = categories Arrows = functors Composition = functor composition Identity = Identity functor
  60. 60. C F D A B C g ∘ f f g
  61. 61. C F D A B C g ∘ f f g F(A)
  62. 62. C F D A B C g ∘ f f g F(A) F(B)
  63. 63. C F D A B C g ∘ f f g F(A) F(B) F(C)
  64. 64. C F D A B C g ∘ f f g F(A) F(B) F(C) F(f)
  65. 65. C F D A B C g ∘ f f g F(A) F(B) F(C) F(f) F(g )
  66. 66. C F D A B C g ∘ f f g F(A) F(B) F(C) F(f) F(g ) F(g ∘ f)
  67. 67. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  68. 68. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  69. 69. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  70. 70. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  71. 71. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  72. 72. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  73. 73. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  74. 74. g ∘ f f g F(f) F(g ) F(g ∘ f) Composition Law F(g ∘ f) = F(g) ∘ F(f)
  75. 75. g ∘ f f g F(f) F(g ) Composition Law F(g ∘ f) = F(g) ∘ F(f) F(g) ∘ F(f)
  76. 76. g ∘ f f g F(f) F(g ) Composition Law F(g ∘ f) = F(g) ∘ F(f) F(g) ∘ F(f) F(g ∘ f)
  77. 77. Identity law F(idA)= idF(A) A
  78. 78. Identity law F(idA)= idF(A) A idA
  79. 79. Identity law F(idA)= idF(A) A idA F(idA)
  80. 80. Identity law F(idA)= idF(A) A
  81. 81. Identity law F(idA)= idF(A) A F(A)
  82. 82. Identity law F(idA)= idF(A) A F(A) idF(A)
  83. 83. Identity law F(idA)= idF(A) A F(A) idF(A) A idA F(idA)
  84. 84. Terminology homomorphism
  85. 85. Terminology homomorphism Same
  86. 86. Terminology homomorphism Same-shape-ism
  87. 87. Terminology homomorphism “structure preserving map”
  88. 88. Terminology homomorphism Functors are “category homomorphisms”
  89. 89. Functors in code trait Functor[F[_]] { def map[A,B](fa: F[A], f: A => B): F[B] }
  90. 90. Functors in code trait Functor[F[_]] { def map[A,B](fa: F[A], f: A => B): F[B] } Objects to objects
  91. 91. Functors in code trait Functor[F[_]] { def map[A,B](fa: F[A], f: A => B): F[B] } Arrows to arrows
  92. 92. Functors in code trait Functor[F[_]] { def map[A,B]: (A => B) => (F[A] => F[B]) } Arrows to arrows
  93. 93. Functors laws in code fa.map(f).map(g) == fa.map(g compose f)
  94. 94. Functors laws in code fa.map(a => a) == fa
  95. 95. Terminology endomorphism
  96. 96. Terminology endomorphism Within
  97. 97. Terminology endomorphism Within -shape-ism
  98. 98. Terminology endomorphism “a mapping from something back to itself”
  99. 99. Terminology endo “a mapping from something back to itself”
  100. 100. Endofunctors In Scala, all our functors are actually endofunctors. Type F Category Category Endofunctor Type
  101. 101. Endofunctors Luckily, we can represent any functor in our type system as some F[_] Type F Category Category Endofunctor Type
  102. 102. List Functor sealed trait List[+A] case class Cons(head: A, tail: List[A]) extends List[A] case object Nil extends List[Nothing]
  103. 103. List Functor sealed trait List[+A] { def map[B](f: A => B): List[B] = this match { case Cons(h,t) => Cons(f(h), t map f) case Nil => Nil } } }
  104. 104. List Functor potatoList .map(mashEm) .map(boilEm) .map(stickEmInAStew)
  105. 105. List Functor userList .map(_.name) .map(_.length) .map(_ + 1) .map(_.toString)
  106. 106. Other functors trait Tree[A] trait Future[A] trait Process[A] trait Command[A] X => A (X, A) trait Option[A]
  107. 107. Functors Fundamental concept in Category Theory Super useful Everywhere Staple of functional programming Write code that’s ignorant of unnecessary context
  108. 108. III. Monoids
  109. 109. Monoids Some set we’ll call M Compose • : M × M  M Identity id : M
  110. 110. Monoid Laws Associative Law (f • g) • h = f • (g • h ) Identity Laws f • id = id • f = f
  111. 111. Category Laws Associative Law (f ∘ g) ∘ h = f ∘ (g ∘ h ) Identity Laws f ∘ id = id ∘ f = f
  112. 112. Monoids Compose • : M × M  M Identity id : M
  113. 113. Category Compose ∘ : (B  C)  (A  B)  (A  C) Identity id : A  A
  114. 114. Category with 1 object Compose ∘ : (A  A)  (A  A)  (A  A) Identity id : A  A
  115. 115. Category with 1 object Compose ∘ : M  M M Identity id : M
  116. 116. Monoids are categories Each arrow is an element in the monoid Only one object
  117. 117. Monoids are categories Objects = placeholder singleton Arrows = elements of the monoid Composition = • Identity = id Only one object Each arrow is an element in the monoid
  118. 118. M H N Monoid Monoid Monoid homomorphism (SM, •M, idM) (SN, •N, idN)
  119. 119. M H N Monoid Monoid Monoid homomorphism (SM, •M, idM) (SN, •N, idN) MonCategory of monoids
  120. 120. M H N Monoid Monoid Monoid homomorphism (SM, •M, idM) (SN, •N, idN) MonCategory of monoids Objects = monoids Arrows = monoid homomorphisms Composition = function composition Identity = Identity function
  121. 121. M H N SM SN “structure-preserving map” Set Set function h Sets Where h preserves composition & identity
  122. 122. Example String length is a monoid homomorphism from (String, +, "") to (Int, +, 0)
  123. 123. Preserves identity Preserves composition "".length == 0 (str1 + str2).length = str1.length + str2.length
  124. 124. Monoids in code trait Monoid[M] { def compose(a: M, b: M): M def id: M }
  125. 125. Monoids in code def foldMonoid[M: Monoid]( ms: Seq[M]): M = { ms.foldLeft(Monoid[M].id) (Monoid[M].compose) }
  126. 126. Int / 0 / + import IntAddMonoid._ foldMonoid[Int](Seq( 1,2,3,4,5,6))  21
  127. 127. Int / 1 / * import IntMultMonoid._ foldMonoid[Int](Seq( 1,2,3,4,5,6))  720
  128. 128. String / "" / + foldMonoid[String](Seq( "alea", "iacta", "est"))  ”aleaiactaest"
  129. 129. Endos / id / ∘ def mash: Potato => Potato def addOne: Int => Int def flipHorizontal: Shape => Shape def bestFriend: Person => Person
  130. 130. A=>A / a=>a / compose foldMonoid[Int => Int](Seq( _ + 12, _ * 2, _ - 3))  (n: Int) => ((n + 12) * 2) - 3
  131. 131. Are chairs monoids?
  132. 132. Chair Composition = You can’t turn two chairs into one Identity =
  133. 133. Chair stack
  134. 134. Chair stack Composition = stack them on top Identity = no chairs
  135. 135. Chair Stack is the free monoid of chairs Protip: just take 0-to-many of anything, and you get a monoid for free
  136. 136. …almost Real monoids don’t topple; they keep scaling
  137. 137. Monoids embody the principle of weakly-typed composability
  138. 138. IV. Products & sums
  139. 139. Algebraic Data Types List[A] - Cons(A, List[A]) - Nil Option[A] - Some(A) - None BusinessResult[A] - OK(A) - Error Wiggles - YellowWiggle - BlueWiggle - RedWiggle - PurpleWiggle Address(Street, Suburb, Postcode, State)
  140. 140. Algebraic Data Types Cons(A × List[A]) + Nil Some(A) + None OK(A) + Error YellowWiggle + BlueWiggle + RedWiggle + PurpleWiggle Street × Suburb × Postcode × State
  141. 141. Algebraic Data Types A × List[A] + 1 A + 1 A + 1 4 Street × Suburb × Postcode × State
  142. 142. Algebraic Data Types A × List[A] + 1 A + 1 A + 1 4 Street × Suburb × Postcode × State isomorphic
  143. 143. Terminology isomorphism
  144. 144. Terminology isomorphism Equal
  145. 145. Terminology isomorphism Equal-shape-ism
  146. 146. Terminology isomorphism “Sorta kinda the same-ish” but I want to sound really smart - Programmers
  147. 147. Terminology isomorphism “Sorta kinda the same-ish” but I want to sound really smart - Programmers
  148. 148. Terminology isomorphism One-to-one mapping between two objects so you can go back-and-forth without losing information
  149. 149. Isomorphism object object arrows
  150. 150. Isomorphism Same as identity
  151. 151. Isomorphism Same as identity
  152. 152. These 4 Shapes Wiggles Set functions Set
  153. 153. These 4 Shapes Wiggles
  154. 154. These 4 Shapes Wiggles
  155. 155. There can be lots of isos between two objects! If there’s at least one, we can say they are isomorphic or A ≅ B
  156. 156. Products A × BA B first seco nd Given the product of A-and-B, we can obtain both A and B
  157. 157. Sums A + BA B left right Given an A, or a B, we have the sum A-or-B
  158. 158. Opposite categories C Cop A B C g ∘ f f g A B C fop ∘ gop fop gop Isomorphic!
  159. 159. A B C g ∘ f f g A B C f ∘ g f g Just flip the arrows, and reverse composition!
  160. 160. A A×B B A product in C is a sum in Cop A sum in C is a product in Cop A+B B A C Cop
  161. 161. Sums ≅ Products!
  162. 162. Terminology dual An object and its equivalent in the opposite category are to each other.
  163. 163. Terminology Co-(thing) Often we call something’s dual a
  164. 164. Terminology Coproducts Sums are also called
  165. 165. V. Composable systems
  166. 166. Growing a system Banana
  167. 167. Growing a system
  168. 168. Growing a system
  169. 169. Growing a system Bunch
  170. 170. Growing a system Bunch Bunch
  171. 171. Growing a system Bunch Bunch Bunch
  172. 172. Growing a system Bunch Bunch Bunch BunchManager
  173. 173. Growing a system Bunch Bunch Bunch BunchManager AnyManagers
  174. 174. compose
  175. 175. compose
  176. 176. etc…
  177. 177. Using composable abstractions means your code can grow without getting more complex Categories and Monoids capture the essence of composition in software!
  178. 178. Look for Monoids and Categories in your domain where you can You can even bludgeon non- composable things into free monoids and free categories
  179. 179. VI. Abstraction
  180. 180. Spanner
  181. 181. Spanner AbstractSpanner
  182. 182. Spanner AbstractSpanner AbstractToolThing
  183. 183. Spanner AbstractSpanner AbstractToolThing GenerallyUsefulThing
  184. 184. Spanner AbstractSpanner AbstractToolThing GenerallyUsefulThing AbstractGenerallyUsefulThingFactory
  185. 185. Spanner AbstractSpanner AbstractToolThing GenerallyUsefulThing AbstractGenerallyUsefulThingFactory WhateverFactoryBuilder
  186. 186. That’s not what abstraction means.
  187. 187. Code shouldn’t know things that aren’t needed.
  188. 188. def getNames(users: List[User]): List[Name] = { users.map(_.name) }
  189. 189. def getNames(users: List[User]): List[Name] = { println(users.length) users.map(_.name) } Over time…
  190. 190. def getNames(users: List[User]): List[Name] = { println(users.length) if (users.length == 1) { s”${users.head.name} the one and only" } else { users.map(_.name) } }
  191. 191. “Oh, now we need the roster of names! A simple list won’t do.”
  192. 192. def getRosterNames(users: Roster[User]): Roster[Name] = { users.map(_.name) }
  193. 193. def getRosterNames(users: Roster[User]): Roster[Name] = { LogFactory.getLogger.info(s”When you party with ${users.rosterTitle}, you must party hard!") users.map(_.name) } Over time…
  194. 194. def getRosterNames(users: Roster[User]): Roster[Name] = { LogFactory.getLogger.info(s"When you party with ${users.rosterTitle}, you must party hard!") if (users.isFull) EmptyRoster("(everyone) ") else users.map(_.name) }
  195. 195. When code knows too much, soon new things will appear that actually require the other stuff.
  196. 196. Coupling has increased. The mixed concerns will tangle and snarl.
  197. 197. Code is rewritten each time for trivially different requirements
  198. 198. def getNames[F: Functor](users: F[User]): F[Name] = { Functor[F].map(users)(_.name) } getNames(List(alice, bob, carol)) getNames(Roster(alice, bob, carol))
  199. 199. Not only is the abstract code not weighed down with useless junk, it can’t be! Reusable out of the box!
  200. 200. Abstraction is about hiding unnecessary information. This a good thing. We actually know more about what the code does, because we have stronger guarantees!
  201. 201. We’ve seen deep underlying patterns beneath superficially different things A×B A+B
  202. 202. Just about everything ended up being in a category, or being one.
  203. 203. There is no better way to understand the patterns underlying software than studying Category Theory.
  204. 204. Further reading Awodey, “Category Theory” Lawvere & Schanuel, “Conceptual Mathematics: an introduction to categories” Jeremy Kun, “Math ∩ Programming” at http://jeremykun.com/ Gabriel Gonzalez “Haskell for all” http://www.haskellforall.com/2012/08/the-category-design- pattern.html http://www.haskellforall.com/2014/04/scalable-program- architectures.html

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