Watch video (in Hebrew): http://parleys.com/play/53f7a9cce4b06208c7b7ca1e
Type classes are a fundamental feature of Scala, which allows you to layer new functionality on top of existing types externally, i.e. without modifying or recompiling existing code. When combined with implicits, this is a truly remarkable tool that enables many of the advanced features offered by the Scala library ecosystem. In this talk we'll go back to basics: how type classes are defined and encoded, and cover several prominent use cases.
A talk given at the Underscore meetup on 19 August, 2014.
2. THE EXPRESSION PROBLEM
“Define a datatype by cases, where one can add new cases to
the datatype and new functions over the datatype, without
recompiling existing code, and while retaining static type
safety (e.g., no casts).”
-- Philip Wadler
8. What’s a Type Class?
• A type class:
– Enables ad-hoc polymorphism
– Statically typed (i.e. type-safe)
– Borrowed from Haskell
• Solves the expression problem:
– Behavior can be extended
– … at compile-time
– ... after the fact
– … without changing/recompiling
existing code
9. Example #1: Equality
• Scala inherits legacy aspects of Java
– This includes AnyRef.equals:
def equals( other: AnyRef ): Boolean
– So the following compiles:
3.14159265359 == "pi" // Evaluates to false
• What if we wanted to implement type-safe equality?
– Let’s define a type-safe isEqual function:
isEqual( 3.14159265359, "pi” ) // Does not compile!
10. What’s in a Type Class?
• Three components are
required:
– A signature
– Implementations for
supported types
– A function that requires
a type class This is where things get hairy.
11. Slight Digression
• A method in Scala can have multiple parameter lists:
def someMethod( x: Int )( y: String )( z: Double ): Unit = {
println( s"x=$x, y=$y, z=$z" )
}
scala> someMethod( 10 )( "abc" )( scala.math.Pi )
x=10, y=abc, z=3.141592653589793
• There are multiple uses for this, but the most important is…
12. Scala Implicits
• The last parameter list of a method can be marked implicit
• Implicit parameters are filled in by the compiler
– In effect, you require evidence of the compiler
– … such as the existence of a type class in scope
– You can also specify parameters explicitly, if needed
13. Putting it together
• Let’s define our type class:
trait Equality[ L, R ] {
def equals( left: L, right: R ): Boolean
}
• … and our isEqual function:
def isEqual[ L, R ]( left: L, right: R )
( implicit ev: Equality[ L, R ] ): Boolean =
ev.equals( left, right )
This is where the magic happens
14. Still missing something!
• We have no implementations of the Equality trait, so nothing works!
scala> isEqual( 3, 3 )
<console>:10: error: could not find implicit value for parameter ev:
Equality[Int,Int]
• We need to implement Equality[ T, T ]:
implicit def sameTypeEquality[ T ] = new Equality[ T, T ] {
def equals( left: T, right: T ) = left.equals( right )
}
• And now it works:
scala> isEqual( 3, 3 )
res1: Boolean = true
15. Ad-hoc Polymorphism
• Now we’ve met our original goal:
scala> isEqual( 3.14159265359, "pi" )
<console>:11: error: could not find implicit value for parameter ev: Equality[Double,String]
• But what if we wanted to equate doubles and strings?
• Well then, let’s add another implementation!
implicit object DoubleEqualsString extends Equality[ Double, String ] {
def equals( left: Double, right: String ) = left.toString == right
}
• Et voila, no recompilation or code changes needed:
scala> isEqual( 3.14159265359, "pi" )
res5: Boolean = false
17. Example #2: Sort Me, Maybe
• Let’s implement a sort
function (e.g. bubble sort)
• With one caveat:
– It should operate on any type
– … for which an ordering exists
• Obviously, we’ll use type
classes!
18. Possible Solution
trait Ordering[ T ] { def isLessThan( left: T, right: T ): Boolean }
def sort[ T ]( items: Seq[ T ] )( implicit ord: Ordering[ T ] ): Seq[ T ] = {
val buffer = mutable.ArrayBuffer( items:_* )
for ( i <- 0 until items.size;
j <- ( i + 1 ) until items.size )
if ( ord.isLessThan( buffer( j ), buffer( i ) ) ) {
val temp = buffer( i )
buffer( i ) = buffer( j )
buffer( j ) = temp
}
buffer
}
19. Possible Solution, cont.
• Sample implementation for integers:
implicit object IntOrdering extends Ordering[ Int ] {
def isLessThan( left: Int, right: Int ) = left < right
}
val numbers = Seq( 4, 1, 10, 8, 14, 2 )
Assert( sort( numbers ) == Seq( 1, 2, 4, 8, 10, 14 ) )
20. Possible Solution, cont.
• Sample implementation for a domain entity:
case class Person( name: String, age: Int )
implicit object PersonOrdering extends Ordering[ Person ] {
def isLessThan( left: Person, right: Person ) =
left.age < right.age
}
val haim = Person( "Haim", 12 )
val dafna = Person( "Dafna", 20 )
val ofer = Person( "Ofer", 1 )
assert( sort( Seq( haim, dafna, ofer ) ) ==
Seq( ofer, haim, dafna ) )
21. Implicit Search Order
Current Scope
• Defined implicits
• Explicit imports
• Wildcard imports
Companion
• … of T
• … of supertypes of T
Outer Scope
• Enclosing class
23. Example #3: Server Pipeline
• REST is good, but annoying to write. Let’s simplify:
case class DTO( message: String )
class MyServlet extends NicerHttpServlet {
private val counter = new AtomicInteger( 0 )
get( "/service" ) {
counter.incrementAndGet()
DTO( "hello, world!" )
}
get( "/count" ) {
counter.get()
}
}
Uses return value;
no direct response manipulation
24. Example #3: Server Pipeline
• What’s in a server?
– Routing
– Rendering
– Error handling
• Let’s focus on rendering:
trait ResponseRenderer[ T ] {
def render( value : T,
request : HttpServletRequest,
response: HttpServletResponse ): Unit
}
25. Example #3: Server Pipeline
• A couple of basic renderers:
implicit object StringRenderer extends ResponseRenderer[ String ] {
def render( value: String, request: HttpServletRequest, response: HttpServletResponse ) = {
val w = response.getWriter
try w.write( value )
finally w.close()
}
}
implicit object IntRenderer extends ResponseRenderer[ Int ] {
def render( value: Int, request: HttpServletRequest, response: HttpServletResponse ) =
implicitly[ ResponseRenderer[ String ] ].render( value.toString, request, response )
}
26. Example #3: Server Pipeline
• Putting it together:
trait NicerHttpServlet extends HttpServlet {
private trait Handler {
type Response
def result: Response
def renderer: ResponseRenderer[ Response ]
}
private var handlers: Map[ String, Handler ] = Map.empty
protected def get[ T : ResponseRenderer ]( url: String )( thunk: => T ) =
handlers += url -> new Handler {
type Response = T
def result = thunk
def renderer = implicitly[ ResponseRenderer[ T ] ]
}
27. Example #3: Server Pipeline
• And finally:
override def doGet( req: HttpServletRequest, resp: HttpServletResponse ) =
handlers.get( req.getRequestURI ) match {
case None =>
resp.sendError( HttpServletResponse.SC_NOT_FOUND )
case Some( handler ) =>
try handler.renderer.render( handler.result, req, resp )
catch { case e: Exception =>
resp.sendError( HttpServletResponse.SC_INTERNAL_SERVER_ERROR )
}
}
29. Example #4: JSON Serialization
• Assume we already have a good model for JSON
• How do we add type-safe serialization?
JsonValue
JsonObject JsonArray
JsonBoolean JsonInt
JsonDouble JsonNull
JsonField
30. Example #4: JSON Serialization
• Let’s start with a typeclass:
trait JsonSerializer[ T ] {
def serialize( value: T ): JsonValue
def deserialize( value: JsonValue ): T
}
• And the corresponding library signature:
def serialize[ T ]( instance: T )( implicit ser: JsonSerializer[ T ] ) =
ser.serialize( instance )
def deserialize[ T ]( json: JsonValue )( implicit ser: JsonSerializer[ T ] ) =
ser.deserialize( json )
31. Example #4: JSON Serialization
• Define a few basic serializers…
implicit object BooleanSerializer extends JsonSerializer[ Boolean ] {
def serialize( value: Boolean ) = JsonBoolean( value )
def deserialize( value: JsonValue ) = value match {
case JsonBoolean( bool ) => bool
case other => error( other )
}
}
implicit object StringSerializer extends JsonSerializer[ String ] {
def serialize( value: String ) = JsonString( value )
def deserialize( value: JsonValue ) = value match {
case JsonString( string ) => string
case other => error( other )
}
}
32. Example #4: JSON Serialization
• We can also handle nested structures
– The compiler resolves typeclasses recursively!
• For example, Option[ T ] :
implicit def optionSerializer[ T ]( implicit ser: JsonSerializer[ T ] ) =
new JsonSerializer[ Option[ T ] ] {
def serialize( value: Option[ T ] ) =
value map ser.serialize getOrElse JsonNull
def deserialize( value: JsonValue ) = value match {
case JsonNull => None
case other => Some( ser.deserialize( other ) )
}
}
Require a serializer for T
… and delegate to it
33. Example #4: JSON Serialization
• What about an arbitrary type?
case class Person( name: String, surname: String, age: Int )
implicit object PersonSerializer extends JsonSerializer[ Person ] {
def serialize( value: Person ) = JsonObject(
JsonField( "name", serialize( value.name ) ),
JsonField( "surname", serialize( value.surname ) ),
JsonField( "age", serialize( value.age ) )
)
def deserialize( value: JsonValue ) = value match {
case obj: JsonObject =>
Person(
name = deserialize[ String ]( obj "name" ),
surname = deserialize[ String ]( obj "surname" ),
age = deserialize[ Int ]( obj "age" )
)
case _ => error( value )
}
}
34. Summary
• We added serialization for Person after the fact without…
– … modifying the serialization framework
– … modifying the domain object
• We did not compromise:
– … type safety or performance
– … modularity or encapsulation
• This applies everywhere!
clients of either are unaffected!
35. … and we’re done
• Thank you for your time!
• Questions/comments?
– tomer@tomergabel.com
– @tomerg
– http://www.tomergabel.com
• Code samples:
– http://git.io/aWc9eQ