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What To Leave Implicit


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Keynote, Scala Days Chicago, April 18, 2017.

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What To Leave Implicit

  1. 1. What to Leave Implicit Martin Odersky Scala Days Chicago April 2017
  2. 2. Con-textual what comes with the text, but is not in the text
  3. 3. Context is all around us - the current configuration - the current scope - the meaning of “<” on this type - the user on behalf of which the operation is performed - the security level in effect …
  4. 4. - globals rigid if immutable, unsafe if mutable - monkey patching - dependency injection at runtime (Spring, Guice) or with macros (MacWire) - cake pattern close coupling + recursion Traditional ways to express context
  5. 5. “Parameterize all the things” The Functional Way
  6. 6. - no side effects - type-safe - fine-grained control Functional is Good
  7. 7. - sea of parameters - most of which hardly ever change - repetitive, boring, prone to mistakes But sometimes it’s too much of a good thing …
  8. 8. If passing a lot of parameters gets tedious, leave some of them implicit. A more direct approach
  9. 9. • If there’s one feature that makes Scala “Scala”, I would pick implicits. • There’s hardly an API without them. • They enable advanced and elegant architectural designs. • They are also misused way too often. Implicits
  10. 10. • takes you through the most common uses of implicits, • gives recommendations of use patterns, • goes through a set of proposed language changes that will make implicits even more powerful and safer to use. This Talk t
  11. 11. • If you do not give an argument to an implicit parameter, one will be provided for you. • Eligible are all implicit values that are visible at the point of call. • If there are more than one eligible candidate, the most specific one is chosen. • If there’s no unique most specific candidate, an ambiguity error Is reported. Ground Rules
  12. 12. • They are a cousin of implicit parameters. • If the type A of an expression does not match the expected type B … Implicit Conversions
  13. 13. • They are a cousin of implicit parameters. • If the type A of an expression does not match the expected type B … … the compiler tries to find an implicit conversion method from A to B. • Same rules as for implicit parameters apply. Implicit Conversions
  14. 14. • Shorthand for defining a new class and an implicit conversion into it. implicit class C(x: T) { … } expands to class C(x: T) { … } implicit def C(x: T) = new C(x) Implicit Classes
  15. 15. • Implicits leverage what the compiler knows about your code. • They remove repetition and boilerplate. • But taken too far, they can hurt readability. When To Use Implicits?
  16. 16. Applicability: Where are you allowed to elide implied information? How do you find out this is happening? Power: What influence does the elided info have? Can it change radically behavior or types? Scope: How much of the rest of the code do you need to know to find out what is implied? Is there always a clear place to look? * Adapted from Rust’s Language Ergonomics Initiative Reasoning Footprint of Implicitness*
  17. 17. Patterns of Implicit Conversions
  18. 18. Extension Methods Discoverability: medium Power: low Scope: large, but IDEs help
  19. 19. Extension Methods Discoverability: medium Power: low Scope: large, but IDEs help
  20. 20. Late Trait Implementation Make existing classes implement new traits without changing their code. This was the original reason for implicits in Scala. Discoverability: low to medium Power: low to medium Scope: large, but IDEs help
  21. 21. They also have some use cases, e.g. • cached implicit classes • context-dependent views What about simple conversions?
  22. 22. • Conversions that go both ways • Conversions that change semantics E.g. collection.convert.WrapAs{Java,Scala} Better: Use Converters collection.convert.DecorateAs{Java,Scala} Anti Patterns
  23. 23. Conversions that undermine type safety Anti Patterns
  24. 24. Conversions between pre-existing types Discoverability: low Power: high Scope: very large Anti Patterns
  25. 25. Discoverability: high Power: low to high Scope: large, but can be explored in IntelliJ Implicit Parameters
  26. 26. Implicit parameters can • prove theorems • establish context • set configurations • inject dependencies • model capabilities • implement type classes Implicit Parameters - Use Cases
  27. 27. Curry Howard isomorphism: Types = Theorems Programs = Proofs C.f. Kennedy & Russo: “Generalized Type Constraints”, OOPSLA 2004 Prove Theorems
  28. 28. Establish Context Example: conference management system. Reviewers should only see (directly or indirectly) the scores of papers where they have no conflict with an author.
  29. 29. Establish Context Example: conference management system. Context is usually stable, can change at specific points.
  30. 30. Configuration & Dependency Management are special cases of context passing. see also: Dick Wall: The parfait pattern
  31. 31. Implement Type Classes Example: Ordering
  32. 32. How can we make implicits better?
  33. 33. What will change: 1. Tighten the rules for implicit conversions 2. Lazy implicits 3. Multiple implicit parameter lists 4. Coherence(?) 5. Implicit function types
  34. 34. 1. Tighten Rules for Implicit Conversions Question: What does this print? Answer: java.lang.IndexOutOfBoundsException: 42 Hint: List[String] <: Function[Int, String]
  35. 35. In the future: Only implicit methods are eligible as conversions. A new class ImplicitConverter allows to abstract over implicit conversions. Converters are turned into conversions like this: 1. Tighten Rules for Implicit Conversions
  36. 36. Implementation Status
  37. 37. 2. Lazy Implicits Problem: When synthesizing code for recursive data structures, we get divergent implicit searches. E.g. will diverge if A expands recursively to Sum[A, B]
  38. 38. 2. Lazy Implicits Solution: Delay the implicit search and tie the recursive knot with a lazy val if a parameter is call-by-name: This change, proposed by Miles Sabin, is a more robust solution than the current “Lazy” type in shapeless.
  39. 39. Implementation Status
  40. 40. 3. Multiple Implicit Parameter Lists Problem: Implicit parameters are currently a bit irregular compared to normal parameters: • there can be only one implicit parameter section • and it must come last. This leads to some awkward workarounds (c.f. Aux pattern). Related problem: It’s sometimes confusing when a parameter is implicit or explicit.
  41. 41. 3. Multiple Implicit Parameter Lists Proposal: • Allow multiple implicit parameter lists • Implicit and explicit parameter lists can be mixed freely. • Explicit application of an implicit parameter must be marked with a new “magic” method, explicitly. • Implementation status: Proposal. Main challenge is migration from current Scala.
  42. 42. 4. Coherence Difference between Scala’s implicits and Haskell’s type classes: The latter are required to be coherent: A type can implement a type class in one way only (globally). This is very restrictive, rules out most of the implicit use cases we have seen. But it also provides some benefits.
  43. 43. Coherence Rules Out Ambiguities Say you have a capability system dealing with driver licences: If you can drive a truck and a cab, you should be able to drive a car. But Scala would give you an ambiguity error.
  44. 44. Coherence Rules Out Ambiguities Proposal: • Allow type classes to declare themselves coherent. • Have the compiler check that coherent traits have only one implementation per type. This is quite tricky. See • Drop all ambiguity checks for coherent implicits.
  45. 45. Parametricity • It turns out that a necessary condition to ensure coherence is to disallow operations like equals, hashCode, isInstanceOf on coherent types. • This restriction is useful in other contexts as well because it gives us “theorems for free”. • Proposal: Change Scala’s top types to: • AnyObj has all of current Any’s methods. Any has only the escape-hatch method asInstanceOf.
  46. 46. Implementation Status
  47. 47. 5. Implicit Function Types Have another look at the conference management system: In a large system, it gets tedious to declare all these implicit Viewers parameters.
  48. 48. Can we do better? Having to write a couple of times does not look so bad. But in the dotty compiler there are > 2600 occurrences of the parameter Would it not be nice to get rid of them?
  49. 49. Towards a solution Let’s massage the definition of viewRankings a bit:
  50. 50. Towards a solution Let’s massage the definition of viewRankings a bit:
  51. 51. Towards a solution Let’s massage the definition of viewRankings a bit: What is its type? So far: Viewers => List[Paper] From now on: implicit Viewers=> List[Paper] or, desugared: ImplicitFunction1[Viewers, List[Paper]]
  52. 52. Inside ImplicitFunction1 ImplicitFunction1 can be thought of being defined as follows: Analogously for all other arities.
  53. 53. Two Rules for Typing 1. Implicit functions get implicit arguments just like implicit methods. Given: val f: implicit A => B implicit val a: A f expands to f(a). 2. Implicit functions get created on demand. If the expected type of b is implicit A => B, then b expands to implicit (_: A) => b
  54. 54. Revised Example Assume: Then reformulate:
  55. 55. Efficiency Implicit function result types can be optimized Instead of creating a closure like this: we can simply create a curried function like this: This brings the cost of implicit functions down to simple implicit parameters.
  56. 56. Implementation Status
  57. 57. • The reader monad is a somewhat popular method to pass context. • Essentially, it wraps the implicit reading in a monad. • One advantage: The reading is abstracted in a type. • But I believe this is shooting sparrows with cannons. • Monads are about sequencing, they have have nothing to do with passing context. The Reader Monad
  58. 58. • allow the same conciseness as the reader monad, • don’t force you into monadic style with explicit sequencing, • are fully composable, • are more than 7x faster than the reader monad. Implicit function types
  59. 59. Neat way to define structure-building DSLs, like this: Natively supported in Groovy and in Kotlin via “receiver functions”. An encore: The Builder Pattern
  60. 60. Scala Implementation
  61. 61. • Any situation where an entity is implicitly understood can be expressed with implicit function types. • We have seen: “The current set of viewers” “The structure to which current code should be added” • Other possibilities: “The current configuration” “The currently running transaction” “The capabilities needed to run this code” "The effects this code has on the outside world” … Conjecture
  62. 62. Find out more on
  63. 63. • Implicit function types are a neat way to abstract over contexts. • It’s a very powerful feature, because it allows one to inject implicit values in a scope simply by defining a type. • I expect it will fundamentally affect the kind of code we will write in the future. Summary (1)
  64. 64. • Implicit parameters are a fundamental and powerful language construct. • They are “just” parameterization, but remove the boilerplate. • One construct  multifaceted use cases • Abstractable using implicit function types. • Implicit conversions are also very convenient, but should be used with care. Summary (2)
  65. 65. When Can I Expect This? Scala 2.12 Scala 2.13 Scala 3.0 TASTY, middle end? stdlib collections dotty MVP dotty 0.x releases 2016 backend, classpath handling Scala 2.14 2017 2018 This is open source work, depends on community’s contributions.  Roadmap is tentative, no promises: “MVP” = minimal viable prototype
  66. 66. Dotty: Dmitry Petrashko Nicolas Stucki Guillaume Martres Sebastien Douraene Felix Mulder Ondrej Lhotak Liu Fengyun Enno Runne Close collaboration with scalac team @ Lightbend: Adriaan Moors Seth Tisue Jason Zaugg Stefan Zeiger Lukas Rytz Credits
  67. 67. Thank You