djspiewak

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

tonymorris

// https://groups.google.com/d/msg/scala-functional/NAMWgC90KLA/sU0rw7ceoQMJ

object ApplyUnapply {

import language.higherKinds // I laugh every time

/*

In order to define Prism, we must define:

paulp

// Quasiquoted excerpt 

  def cdef = q"""
    class $ClassName[..$classTypeParams](..$primaryParams) extends ..$classParents {
      ..$primaryAccessors

      def get = this
      def isEmpty = ${quasi.isEmpty}
      def copy(..$primaryWithDefaults) = $ObjectName(..$primaryNames)

henkerik

import scala.language.higherKinds
import scalaz.Coproduct
import scalaz.Functor
import scalaz.Applicative
import scalaz.Free
import scalaz.Free.Return
import scalaz.Free.Suspend
import scalaz.State.modify
import scalaz.State
import scalaz.Monad

tonymorris

object SKI_Applicative {
/*
First, let's talk about the SK combinator calculus and how it contributes to solving your problem.

The SK combinator calculus is made of two functions (aka combinators): S and K. It is sometimes called the SKI combinator calculus, however, the I combinator can be derived from S and K. The key observation of SK is that it is a turing-complete system and therefore, anything that can be expressed as SK is also turing-complete. Here is a demonstration that Scala's type system is turing-complete (and therefore, undecidable) for example[1].

The K combinator is the most trivial of the two. It is sometimes called "const" (as in Haskell). There is also some discussion about its evaluation strategy in Scala and how to best express it[2]. The K function might be paraphrased as, "takes a value and returns a (constant) unary function that always returns that value."
*/
  def k[A, B]: A => B => A =
    a => _ => a

xeno-by

Answers http://stackoverflow.com/questions/10373318/mixing-in-a-trait-dynamically.

Compile as follows:
scalac Common_1.scala Macros_2.scala
scalac Common_1.scala Test_3.scala -cp <path to the result of the previous compilation>

Tested in 2.10.0-M3, will most likely not compile by the time 2.10.0 final is released, because we're actively rehashing the API. 
However the principles will remain the same in the final release, so the concept itself is okay.
upd. Code updated for 2.10.0-M7.
upd. Code updated for 2.10.0-RC1.

sauloarruda

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