State of the functional ecosystem in Kotlin: Mid-2018 checkup

In this talk we’ll go through several of the new patterns and libraries that the Arrow organization is helping grow in the Kotlin community.

Starting from the perspective of someone without experience in functional languages and idioms, what problems are these functional libraries trying to solve, and how do they compare to existing libraries. Lastly, we’ll go through some of the examples and resources available online for those who work on libraries and infrastructure.

Transcript

1. @pacoworks Paco Estevez State of the functional ecosystem in Kotlin: Mid-2018 checkup
2. @pacoworks We’re growing our tools We’re improving our ecosystem We want all of you to be part of it 2
3. @pacoworks Where does Arrow fit in your day to day code? Looking past the basic constructs What projects are using Arrow, today 3
4. @pacoworks Building functional intuition 4
5. @pacoworks This is readable fun deepUpdate(m: Meetup, f: (Id) -> Id) { val l = ArrayList() for (talk in m.talks) { val newAtt = ArrayList() for (attendee in talk.attendees) { newAtt += Attendee(id = f(attendee.id)) } l += talk.copy(attendees = newAtt.toList()) } m.copy(talks = list.toList()) } 5 Two mutations, plenty of lines
6. @pacoworks This is readable familiar fun deepUpdate(m: Meetup, f: (Id) -> Id) { val l = ArrayList() for (talk in m.talks) { val newAtt = ArrayList() for (attendee in talk.attendees) { newAtt += Attendee(id = f(attendee.id)) } l += talk.copy(attendees = newAtt.toList()) } m.copy(talks = list.toList()) } 6 Two mutations, plenty of lines
7. @pacoworks This can become familiar fun deepUpdate(m: Meetup, f: (Id) -> Id) = m.copy(talks = m.talks.map { it.attendees.map { it.copy(id = f(it.id)) } }) 7
8. @pacoworks This can become familiar fun deepUpdate(m: Meetup, f: (Id) -> Id) = Meetup.talks.every().attendees.every().id { meetup.modify(f) } 8
9. @pacoworks Myths and misconceptions No magic: function composition Not a complex stream with internal state and threads Replaced in tests by a function or implementing an interface with 1-3 methods 9 Of getter/setter for this example!
10. @pacoworks Most common question 10
11. @pacoworks How is the performance? Runtime performance? Compile-time performance? Development time performance? Debug time performance? 11 Same as hand rolling it, except we’ve already done it. Can be hand-rolled with our abstractions, annotation processed, or even checked into the repo Net perf improvement. LARGE. Pure function composition, only the input parameters can fail.
12. @pacoworks Tackling the ordinary with Arrow 12
13. @pacoworks API design concerns I don’t want to write a new class every time a function has multiple returns My function return can fail, throw, or branch out I need this function to be lazy or cache its results Our Android app cannot take one more library! 13
14. @pacoworks arrow-core I don’t want to write a new class every time a function has multiple returns Tuples 14 fun initializeSubsystems(): Tuple2<Database, Network> Up to 21 elements Starter
15. @pacoworks arrow-core My function return can fail, throw, or branch out Either, Option, Try 15 fun find(l: List<A>, f: (A) -> Boolean): Option<Tuple2<Int, A>> Starter
16. @pacoworks arrow-core I need this function to be lazy or cache its results Eval 16 fun foldRight(lb: Eval<B>, f: (A, Eval<B>) -> Eval<B>): Eval<B> Starter
17. @pacoworks arrow-data Collections and wrappers NonEmptyList, ListK, MapK, SetK… Read dependencies, write to logs, carry over state Reader, Writer, State Compose datatypes Transformers 17 Starter
18. @pacoworks How do I handle functions like data? 18 val fIntToInt: (Int) -> Int = { p: Int -> p + 1 } val fIntToString: (Int) -> String = { it.toString() } val fIntAndIntToInt: (Int, Int) —> Int = { p: Int, q: Int -> p + q }
19. @pacoworks How NOT to handle functions like data 19 { fIntToInt(fIntToInt(it)) } { fIntToString(fIntToInt(it)) } { p: Int, q: Int -> fIntToInt(fIntAndIntToInt(p,q)) } { p: Int, _: Int -> p + 10 }
20. @pacoworks arrow-syntax 20 0 -> fIntToInt andThen fIntToInt // 2 2 -> fIntToString compose fIntToInt // “3” 2, 3 -> fIntAndIntToInt andThen fIntToInt // 6 2 -> fIntAndIntToInt apply 10 // 12 Tuple2(2, 3) -> fIntAndIntToInt.paired() // 5 fIntToExpensive.memoize() -> is called pipe Starter
21. @pacoworks Easing the bigger ideas 21
22. @pacoworks Working with plain data Data classes: accessing fields Sealed classes: matching with when or fold Collections: traversing elements Maps: accessing elements Option and Either 22
23. @pacoworks Throwback Slide Meetup.talks.every().attendees.every().id { meetup.modify(f) } 23
24. @pacoworks Functions all the way down IdSetter compose ListEach<Attendee> compose AttendeesSetter compose ListEach<Talks> compose TalkSetter compose MeetupSetter 24
25. @pacoworks Working in your domain @optics sealed class NetworkResult @optics data class Success(val content: Meetup): NetworkResult() @optics sealed class NetworkError : NetworkResult() @optics data class HttpError(val message: String): NetworkError() object TimeoutError: NetworkError() 25
26. @pacoworks More of the same NetworkResult.success.meetup.talks.every().attendees.every().id { result.getOrModify() } NetworkResult.networkError.httpError.message { result.getOrModify() } 26
27. @pacoworks arrow-optics Do I need to access a field? Do I need to modify a field? Can I match just this one sealed class? Can I get the element at index I? Can I update just the value at key K? 27 Interm ediate
28. @pacoworks Seeing the forest val projects = MultiProjects(“All”, NonEmptyList( Project(“optics”, Budget(100)), MultiProjects(“Basics”, NonEmptyList( Project(“core”, Budget(1)), Project(“data”, Budget(5)), )), Project(“generic”, Budget(75)), )) 28
29. @pacoworks Seeing trees sealed class Project<A> data class MultiProjects<A>( val category: String, val l: NonEmptyList<Project<A>> ): Project<A>() data class SingleProject(val name: String, val info: A) data class Budget(moneys: Int) val projects: Project<Budget> = ... 29
30. @pacoworks arrow-recursion Abstraction for recursive data structures, including lists and trees Adds helper functions to traverse, fold, and map these structures Special thanks to Aedan Smith 30 Advanced
31. @pacoworks Constructing and deconstructing data Serialization is a hard problem Deserialization is even worse! Extension functions for simple data? 31
32. @pacoworks Structural types 32 data class Account(val id: Int, val name: String, val balance: Int) typealias AccountTuple = Tuple3<Int, String, Int> typealias AccountHList = HCons<Int, HCons<String, HCons<Int, HNil>>>
33. @pacoworks arrow-generic 33 @product data class Account(...) account.tupled() account.toHList() account + account (account, account, account).combineAll() Early days Interm ediate
34. @pacoworks Are my abstractions anaemic? “I wish I had that RxJava operator for this” Duplicated code per class per design pattern or operator Shapes for generics don’t quite fit 34 getUserById(id) .flatMap { user -> Observable.merge( user.friends.map { friend -> getUserById(friend.id) } ).toList() }
35. @pacoworks Extension interfaces Many of your classes will get lots of helpers if they implement certain functions: map: gets you another 6 extension functions foldLeft: gives 17! new extension functions flatMap: adds 8 extension functions and access to comprehensions 35
36. @pacoworks New functionality for everyone 36 Option<Option<Companies>> -> Option<Companies> // Monad#flatten Try<Id>, Try<Name>, Try<Count> -> Try<Tuple3<Id, Name, Count>> // Applicative#tupled SetK<User>, (User -> Boolean) -> Option<User> // Foldable#find ListK<DeferredK<UserDto>> -> DeferredK<List<UserDto>> MapK<Id, Either<Error, User>> -> Either<Error, Map<Id, User>> // Traverse#sequence
37. @pacoworks Comprehensions for everyone 37 bindingCatch { val user = getUserById(id).bind() val friendProfiles = user.friends.map { getUserById(it.id).bind() } friendProfiles }
38. @pacoworks Coding to the interface 38 interface Dependencies<F>: MonadError<F>, Traverse<F>, Eq<Team>, ProvidesNetwork fun <F> Dependencies<F>.requestTeams( ids: List<TeamId> ): Kind<F, List<Team>> = ...
39. @pacoworks Coding to the interface 39 tryDeps.requestTeams(listOf(1,2,3)).fix() // Try<List<Team>> eitherDeps.requestTeams(listOf(1,2,3)).fix() // Either<Throwable, List<Team>> optionDeps.requestTeams(listOf(1,2,3)).fix() // Option<List<Team>>
40. @pacoworks arrow-typeclasses Interfaces defining extension functions that can be implemented using 1-3 new functions You can replace concrete classes with these interfaces for generic behavior Extensive test suite rooted on CS theory 40 Interm ediate
41. @pacoworks 41
42. @pacoworks Dependency Management 42 arrow-instances-(core, data) provides implementations of typeclasses for datatypes coming from Arrow arrow-dagger-* provides Modules to inject those instances using Dagger 2 Interm ediate
43. @pacoworks arrow-effects val obs: ObservableKW<List<User>> = getUserFriends(“123”).fix() val io: IO<List<User>> = getUserFriends(“123”).fix() val def: Deferred<List<User>> = getUserFriends(“123”).fix() 43 Generic behavior for threading and side-effects across frameworks Same expectations for operators Shared test suite Starter
44. @pacoworks arrow-free 44 Interpreter for operation DSLs Synchronous, asynchronous, parallel, or sequential execution Debug, print as a string, optimize… Advanced
45. @pacoworks Growing an ecosystem 45
46. @pacoworks Ank Available arrow/ank 46 Verify your docs by compiling snippets Output the results of snippets in the docs themselves Available for Java and Kotlin Built with arrow-free
47. @pacoworks Helios Alpha 47deg/helios 47 A screaming fast JSON library DSL syntax Extension via typeclasses Built with arrow-optics and arrow-generic
48. @pacoworks Kollect Alpha 47deg/kollect 48 A data access library for databases and network Allows paralellisation, caching, batching Built with arrow-effects and arrow-free
49. @pacoworks Kor Stable Sefford/kor 49 A clean architecture implementation Includes Use Cases and Repositories Built with arrow-core and arrow-data
50. @pacoworks Kessel Pre-alpha xenomachina/kessel 50 Parser combinator library Provides tokenizator and parsing Future migration to GLL parsing Built with arrow-core and arrow-data
51. @pacoworks arrow-streams Pre-alpha 51 An abstraction over reactive streams across libraries Configuration for your own effect and executor abstraction Built with arrow-effects
52. @pacoworks arrow-android? Preproduction 52 Input accepted :D
53. @pacoworks Sharing understanding 53
54. @pacoworks Arrow Docs arrow-kt.io/docs/ 54 Large community project Tens of contributors Contributing is a great way to learn!
55. @pacoworks FP in Kotlin with Arrow youtu.be/1h4X8CrMjVs 55 Video series on youtube Linked atop of each doc Bi-weekly releases
56. @pacoworks Talks, books and courses arrow-kt.io/docs/ quickstart/blogs/ 56 Functional Kotlin @ pakt Functional programming in Kotlin with Arrow @ caster.io Kotlin Funcional @ Functionalhub Hands On Functional Kotlin @ udemy
57. @pacoworks Community <3 gitter.im/arrow-kt/ 57 73 github contributors Gitter.im chat Kotlinlang slack #arrow
58. @pacoworks Arrow: arrow-kt.io pacoworks.com @pacoworks github.com/pakoito Slides: tinyurl.com/ArrowKotliners18 58 Special thanks to all Arrow contributors & supporters!