Scala - monads

作者: pangolulu | 来源:发表于2016-04-17 17:21 被阅读158次

    Monads

    带有mapflatMap方法的数据结构很常见。实际上,there’s a name that describes this class of a data structures together with some algebraic laws that they should have. 他们称作Monads。
    那么,什么是Monad?What is Monad?

    A monad M is a parametric type M[T] with two operations, flatMap and unit, that have to satisfy some laws.

    trait M[T] {
      def flatMap[U](f: T => M[U]): M[U]
    }
    def unit[T](x: T): M[T]
    

    通常Monad中的flatMap称作bind

    Examples of Monads

    下面列举了Scala中的一些Monads,

    1. List is a monad with unit(x) = List(x)
    2. Set is monad with unit(x) = Set(x)
    3. Option is a monad with unit(x) = Some(x)
    4. Generator is a monad with unit(x) = single(x)

    这些类型中都包含了同样的flatMap方法,然而unit方法对于每个monad都要不同定义。

    Monads and Map

    对于每个monad,可以通过flatMapunit来定义map,即:

    m map f == m flatMap (x => unit(f(x))) == m flatMap (f andThen unit)
    

    andThen方法在表示函数的组合,f andThen unit表示首先执行函数f接着执行函数unit

    Monad Laws

    To qualify as a monad, a type has to satisfy three laws:

    1. Associativity:
    (m flatMap f) flatMap g == m flatMap (x => f(x) flatMap g)
    
    1. Left unit
    unit(x) flatMap f == f(x)
    
    1. Right unit
    m flatMap unit == m
    

    Example of Checking Monad Laws

    下面举一个例子,证明Option符合monad laws。首先给出OptionflatMap的定义。

    abstract class Option[+T] {
      def flatMap[U](f: T => Option[U]): Option[U] = this match {
        case Some(x) => f(x)
        case None => None
      }
    }
    
    • Checking the Left Unit Law
      首先来证明Left Unit Law,也就是证明unit(x) flatMap f == f(x),由于OptionUnit定义为unit(x) = Some(x),故证明Some(x) flatMap f == f(x)
       Some(x) flatMap f ==
       Some(x) match {
         case Some(x) => f(x)
         case None => None
       } == f(x)
    
    • Checking the Right Unit Law
      证明Right Unit Law,也就是证明m flatMap unit == m,即证明m flatMap Some == m
       m flatMap Some ==
       m match {
         case Some(x) => Some(x)
         None => None
       } == m
    
    • Checking the Associative Law
      最后,证明Associative Law,也就是证明(m flatMap f) flatMap g == m flatMap (x => f(x) flatMap g)
       (m flatMap f) flatMap g ==
       m match { case Some(x) => f(x) case None => None }
         match { case Some(y) => g(y) case None => None } ==
         m match {
         case Some(x) => f(x) match { case Some(y) => g(y) case None => None }
         case None => None match { case Some(y) => g(y) case None => None }
       } ==
       m match {
         case Some(x) => f(x) match { case Some(y) => g(y) case None => None }
         case None => None
       } ==
       m match {
         case Some(x) => f(x) flatMap g
         case None => None
       } == m flatMap (x => f(x) flatMap g)
    

    Significance of the Laws for For-Expressions

    1. Associativity says essentially that one can “inline” nested for expressions:
    for (y <- for (x <- m; y <- f(x)) yield y; z <- g(y)) yield z ==
    for (x <- m; y <- f(x); z <- g(y)) yield z
    
    1. Right unit says:
       for (x <- m) yield x == x
    
    1. Left unit does not have an analogue for for-expressions.

    Another type: Try

    在后面的课程里将会用到的一个类型就是Try,他的定义如下:

    abstract class Try[+T]
    case class Success[T](x: T) extends Try[T]
    case class Failure(ex: Exception) extends Try[Nothing]
    

    在Scala中Nothing是所有类型的子类型,一般用来表示什么都没有返回,如发生了异常。
    对于Try的作用有如下解释:

    Try is used to pass results of computations that can fail with an exception between threads and computers.

    也就是说异常的传播可以不是通过调用栈,而是在不同的thread,不同的机器上进行传播。

    你可以在Try中封装任何计算,也就是说:

    Try(expr) // gives Success(someValue) or Failure(someException)
    

    为了支持上面的创建Try对象的语法,需要定义TryObject类型,并且实现apply方法。apply方法类似于()的方法名。如下所示:

    object Try {
      def apply[T](expr: => T): Try[T] =
        try Success(expr)
        catch {
          case NonFatal(ex) => Failure(ex)
        }
      }
    }
    

    其中的参数传递语法expr: => T表示call by name,也就是说传递参数时并不先进行evaluate求值,直到进入try Success(expr)才进行evaluate,这也是可以在apply内部捕捉到异常的原因。

    就像Option类型一样,Try也可以使用for表达式。比如:

    for {
      x <- computeX
      y <- computeY
    } yield f(x, y)
    

    如果computeXcomputeY成功运行得到结果Success(x)和结果Success(y),那么该表达式返回Success(f(x, y));如果上面两个运算只要有一个出现错误,该表达式返回Failure(ex)

    为了支持for表达式,需要在Try类型上定义mapflatMap方法。定义如下所示:

    abstract class Try[T] {
      def flatMap[U](f: T => Try[U]): Try[U] = this match {
        case Success(x) => try f(x) catch { case NonFatal(ex) => Failure(ex) }
        case fail: Failure => fail
      }
      
      def map[U](f: T => U): Try[U] = this match {
        case Success(x) => Try(f(x))
        case fail: Failure => fail
      }
    }
    

    其实,map是可以由flatMap定义的:

    t map f == t flatMap (x => Try(f(x))) == t flatMap (f andThen Try)
    

    问题来了,定义了unit = Try后,Try是不是一个monad呢?答案是:不符合left unit law,也就是Try(expr) flatMap f != f(expr)。为什么呢?课上给的解释是:

    Indeed the left-hand side will never raise a non-fatal exception whereas the right-hand side will raise any exception thrown by expr or f.

    Left unit does not have an analogue for for-expressions这条结论可以验证,即使Try违法了left unit law他也可以使用for表达式。

    Monad这一概念很抽象,也不怎么好理解,需要在以后的课程中使用Monad的特性来加深对Monad的认识。

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