1. 程式人生 > >深圳scala-meetup-20180902(2)- Future vs Task and ReaderMonad依賴注入

深圳scala-meetup-20180902(2)- Future vs Task and ReaderMonad依賴注入

  在對上一次3月份的scala-meetup裡我曾分享了關於Future在函式組合中的問題及如何用Monix.Task來替代。具體分析可以查閱這篇博文。在上篇示範裡我們使用了Future來實現某種non-blocking資料庫操作,現在可以用Task替換Future部分:

  class KVStore[K,V] {
    private val kvs = new ConcurrentHashMap[K,V]()
    def create(k: K, v: V): Task[Unit] = Task.delay(kvs.putIfAbsent(k,v))
    def read(k: K): Task[Option[V]] = Task.delay(Option(kvs.get(k)))
    def update(k: K, v: V): Task[Unit] = Task.delay(kvs.put(k,v))
    def delete(k: K): Task[Boolean] = Task.delay(kvs.remove(k) != null)
  }

Task是一個真正的Monad,我們可以放心的用來實現函式組合:

  type FoodName = String
  type Quantity = Int
  type FoodStore = KVStore[String,Int]

  def addFood(food: FoodName, qty: Quantity)(implicit fs: FoodStore): Task[Quantity] = for {
    current <- fs.read(food)
    newQty = current.map(cq => cq + qty).getOrElse(qty)
    _ <- fs.update(food,newQty)
  } yield newQty

  def takeFood(food: FoodName, qty: Quantity)(implicit fs: FoodStore): Task[Quantity] = for {
    current <- fs.read(food)
    cq = current.getOrElse(0)
    taken = Math.min(cq,qty)
    left = cq - taken
    _ <- if(left > 0) fs.update(food,left) else fs.delete(food)
  } yield taken


  def cookSauce(qty: Quantity)(get: (FoodName,Quantity) => Task[Quantity],
                               put: (FoodName,Quantity) => Task[Quantity]): Task[Quantity] = for {
    tomato <- get("Tomato",qty)
    vaggies <- get("Veggies",qty)
    _ <- get("Galic",10)
    sauceQ = tomato/2 + vaggies * 3 / 2
    _ <- put("Sauce",sauceQ)
  } yield sauceQ

  def cookPasta(qty: Quantity)(get: (FoodName,Quantity) => Task[Quantity],
                               put: (FoodName,Quantity) => Task[Quantity]): Task[Quantity] = for {
    pasta <- get("Pasta", qty)
    sauce <- get("Sauce", qty)
    _ <- get("Spice", 3)
    portions = Math.min(pasta, sauce)
    _ <- put("Meal", portions)
  } yield portions

跟上次我們使用Future時的方式沒有兩樣。值得研究的是如何獲取Task運算結果,及如何更精確的控制Task運算如取消執行中的Task:

  implicit val refridge = new FoodStore

  val shopping: Task[Unit] = for {
    _ <- addFood("Tomato",10)
    _ <- addFood("Veggies",15)
    _ <- addFood("Garlic", 42)
    _ <- addFood("Spice", 100)
    _ <- addFood("Pasta", 6)
  } yield()

  val cooking: Task[Quantity] = for {
    _ <- shopping
    sauce <- cookSauce(10)(takeFood(_,_),addFood(_,_))
    meals <- cookPasta(10)(takeFood(_,_),addFood(_,_))
  } yield meals

 import scala.util._
  import monix.execution.Scheduler.Implicits.global

  val cancellableCooking = Cooking.runOnComplete { result =>
    result match {
      case Success(meals) => println(s"we have $meals pasta meals for the day.")
      case Failure(err) => println(s"cooking trouble: ${err.getMessage}")
    }
  }

  global.scheduleOnce(1 second) {
    println(s"its taking too long, cancelling cooking ...")
    cancellableCooking.cancel()
  }

在上面例子裡的addFood,takeFood函式中都有個fs:FoodStore引數。這樣做可以使函式更加通用,可以對用不同方式實施的FoodStore進行操作。這裡FoodStore就是函式的依賴,我們是通過函式引數來傳遞這個依賴的。重新組織一下程式碼使這種關係更明顯:

  class Refridge {
    def addFood(food: FoodName, qty: Quantity): FoodStore => Task[Quantity] = { foodStore =>
      for {
        current <- foodStore.read(food)
        newQty = current.map(c => c + qty).getOrElse(qty)
        _ <- foodStore.update(food, newQty)
      } yield newQty
    }

    def takeFood(food: FoodName, qty: Quantity): FoodStore => Task[Quantity] = { foodStore =>
      for {
        current <- foodStore.read(food)
        cq = current.getOrElse(0)
        taken = Math.min(cq, qty)
        left = cq - taken
        _ <- if (left > 0) foodStore.update(food, left) else foodStore.delete(food)
      } yield taken
    }

  }

現在我們用一個函式型別的結果來代表依賴注入。這樣做的好處是簡化了函式主體,徹底把依賴與函式進行了分割,使用函式時不必考慮依賴。

scala的函式式元件庫cats提供了一個Kleisli型別,reader monad就是從它推匯出來的:

 final case class Kleisli[M[_], A, B](run: A => M[B]) { self =>
 ...
 trait KleisliFunctions {
   /**Construct a Kleisli from a Function1 */
   def kleisli[M[_], A, B](f: A => M[B]): Kleisli[M, A, B] = Kleisli(f)
 …
  def >=>[C](k: Kleisli[M, B, C])(implicit b: Bind[M]): Kleisli[M, A, C] =  
          kleisli((a: A) => b.bind(this(a))(k.run))
 …
 Kleisli的用途就是進行函式的轉換
 // (A=>M[B]) >=> (B=>M[C]) >=> (C=>M[D]) = M[D]

實際上Kleisli就是ReaderT:

 type ReaderT[F[_], E, A] = Kleisli[F, E, A]
 val ReaderT = Kleisli
 val reader = ReaderT[F,B,A](A => F[B]) 
 val readerTask = ReaderT[Task,B,A](A => Task[B])
 val injection = ReaderT { foodStore => Task.delay { foodStore.takeFood } }
 val food = injection.run(db) // run(kvs), run(dbConfig) …

這段程式碼裡我們也針對上面的例子示範了ReaderT的用法。現在我們可以把例子改成下面這樣:

  type FoodName = String
  type Quantity = Int
  type FoodStore = KVStore[String,Int]

  class Refridge {
    def addFood(food: FoodName, qty: Quantity): ReaderT[Task,FoodStore,Quantity] = ReaderT{ foodStore =>
      for {
        current <- foodStore.read(food)
        newQty = current.map(c => c + qty).getOrElse(qty)
        _ <- foodStore.update(food, newQty)
      } yield newQty
    }

    def takeFood(food: FoodName, qty: Quantity): ReaderT[Task,FoodStore,Quantity] = ReaderT{ foodStore =>
      for {
        current <- foodStore.read(food)
        cq = current.getOrElse(0)
        taken = Math.min(cq, qty)
        left = cq - taken
        _ <- if (left > 0) foodStore.update(food, left) else foodStore.delete(food)
      } yield taken
    }

  }

ReaderT[F[_],E,A]就是ReaderT[Task,FoodStore,Quantity]. FoodStore是注入的依賴,ReaderT.run返回Task:

  val cooking: ReaderT[Task,FoodStore,Quantity] = for {
    _ <- shopping
    sauce <- cooker.cookSauce(10)
    pasta <- cooker.cookPasta(10)
  } yield pasta

  import scala.concurrent.duration._
  import scala.util._
  import monix.execution.Scheduler.Implicits.global
  val timedCooking = cooking.run(foodStore).timeoutTo(1 seconds, Task.raiseError( new RuntimeException(
    "oh no, take too long to cook ...")))
  val cancellableCooking = timedCooking.runOnComplete { result =>
    result match {
      case Success(meals) => println(s"we have $meals specials for the day.")
      case Failure(exception) => println(s"kitchen problem! ${exception.getMessage}")
    }
  }
  global.scheduleOnce(3 seconds) {
    println("3 seconds passed,cancelling ...")
    cancellableCooking.cancel()
  }

我們知道cooking是個ReaderT,用run(foodStore)來注入依賴foodStore。那麼如果我們還有一個kvStore或者jdbcDB,mongoDB可以直接用run(kvStore), run(jdbcDB), run(mongoDB) ... 返回的結果都是Task。