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深圳scala-meetup-20180902(2)- Future vs Task and ReaderMonad依赖注入

  在对上一次3月份的scala-meetup里我曾分享了关于Future在函数组合中的问题及如何用Monix.Task来替代。具体分析可以查阅这篇博文。在上篇示范里我们使用了Future来实现某种non-blocking数据库操作,现在可以用Task替换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是一个真正的Monad,我们可以放心的用来实现函数组合:

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

跟上次我们使用Future时的方式没有两样。值得研究的是如何获取Task运算结果,及如何更精确的控制Task运算如取消运行中的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() }

在上面例子里的addFood,takeFood函数中都有个fs:FoodStore参数。这样做可以使函数更加通用,可以对用不同方式实施的FoodStore进行操作。这里FoodStore就是函数的依赖,我们是通过函数参数来传递这个依赖的。重新组织一下代码使这种关系更明显:

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 } }

现在我们用一个函数类型的结果来代表依赖注入。这样做的好处是简化了函数主体,彻底把依赖与函数进行了分割,使用函数时不必考虑依赖。

scala的函数式组件库cats提供了一个Kleisli类型,reader monad就是从它推导出来的:

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的用途就是进行函数的转换 // (A=>M[B]) >=> (B=>M[C]) >=> (C=>M[D]) = M[D]

实际上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) …

这段代码里我们也针对上面的例子示范了ReaderT的用法。现在我们可以把例子改成下面这样:

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是注入的依赖,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() }

我们知道cooking是个ReaderT,用run(foodStore)来注入依赖foodStore。那么如果我们还有一个kvStore或者jdbcDB,mongoDB可以直接用run(kvStore), run(jdbcDB), run(mongoDB) ... 返回的结果都是Task。

 

欢迎阅读本文章: 陶远忠

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