Akka Notes – Finite State Machines – 2
In the first part of notes on Akka FSM, we saw the basics of Akka FSM and the outline of the Coffee vending machine that we planned to build – the structure of the Actor and a list of messages we pass to the Actor. In this second and final part, we will go ahead and implement each of these States.
Recap
As a quick recap, let’s look at the structure of the FSM and the messages that can be sent to it.
States and Data
The three States of the FSM and the Data being sent across the States are :
object CoffeeMachine { sealed trait MachineState case object Open extends MachineState case object ReadyToBuy extends MachineState case object PoweredOff extends MachineState case class MachineData(currentTxTotal: Int, costOfCoffee: Int, coffeesLeft: Int) }
Messages
The Vendor and User Interaction messages that we send to the FSM are :
object CoffeeProtocol { trait UserInteraction trait VendorInteraction case class Deposit(value: Int) extends UserInteraction case class Balance(value: Int) extends UserInteraction case object Cancel extends UserInteraction case object BrewCoffee extends UserInteraction case object GetCostOfCoffee extends UserInteraction case object ShutDownMachine extends VendorInteraction case object StartUpMachine extends VendorInteraction case class SetNumberOfCoffee(quantity: Int) extends VendorInteraction case class SetCostOfCoffee(price: Int) extends VendorInteraction case object GetNumberOfCoffee extends VendorInteraction case class MachineError(errorMsg:String) }
Structure of FSM Actor
Here’s the overall structure that we saw in Part 1
class CoffeeMachine extends FSM[MachineState, MachineData] { //What State and Data must this FSM start with (duh!) startWith(Open, MachineData(..)) //Handlers of State when(Open) { ... ... when(ReadyToBuy) { ... ... when(PoweredOff) { ... ... //fallback handler when an Event is unhandled by none of the States. whenUnhandled { ... ... //Do we need to do something when there is a State change? onTransition { case Open -> ReadyToBuy => ... ... ... }
Initial State
As with any State Machine, an FSM needs an initial state to start with. This can be declared inside Akka FSM in a very intuitive method named startWith
. The startWith
accepts two arguments – the initial state and the initial data.
class CoffeeMachine extends FSM[MachineState, MachineData] { startWith(Open, MachineData(currentTxTotal = 0, costOfCoffee = 5, coffeesLeft = 10)) ... ...
The above code just says that the FSM’s initial state is Open
and the initial data while the Coffee machine is opened is MachineData(currentTxTotal = 0, costOfCoffee = 5, coffeesLeft = 10)
.
Since the machine has just started, the vending machine starts with a clean slate. It had no interaction with any user yet and therefore the current showing balance for this transaction is 0. The price of the coffee is set at $5 and the total number of coffees that the machine could vend in total is 10. Once the coffees has vended 10 coffees and is left with 0, the machine shuts down.
Implementing the States
Ah, Finally !!
I felt that the easiest way to look at the interactions with the vending machine at different states is by grouping the interactions, write testcases around it and accompany that with the implementation in the FSM.
If you are referring to the github code, all tests are in the CoffeeSpec and the FSM is the CoffeeMachine
All the following tests are wrapped inside the CoffeeSpec test class whose declaration goes like :
class CoffeeSpec extends TestKit(ActorSystem("coffee-system")) with MustMatchers with FunSpecLike with ImplicitSender
Setting and Getting Price of coffee
As we saw above, the MachineData is initiated at $5 dollars per coffee and with a capacity of 10 coffees. This is just an initial state. The Vendor must have the capacity to set the price of the coffee and the capacity of the machine at any point of time.
Setting of price is achieved by sending the SetCostOfCoffee
message to the Actor. We should also have the ability to get the price of coffee. This is done by using the GetCostOfCoffee
message to which the Machine responds with the currently set price.
Testcase
describe("The Coffee Machine") { it("should allow setting and getting of price of coffee") { val coffeeMachine = TestActorRef(Props(new CoffeeMachine())) coffeeMachine ! SetCostOfCoffee(7) coffeeMachine ! GetCostOfCoffee expectMsg(7) } ... ... ...
Implementation
Like we discussed in Part 1, every message that is being sent to the FSM is received and wrapped in an Event
class which also wraps around the MachineData
:
when(Open) { case Event(SetCostOfCoffee(price), _) => stay using stateData.copy(costOfCoffee = price) case Event(GetCostOfCoffee, _) => sender ! (stateData.costOfCoffee); stay() ... ... } }
There are a few words which are new in the above code – stay
, using
and stateData
. Let’s look at them in detail.
stay
and goto
The idea is that each of the case
blocks in a state must return a State
. This could either be done using stay
which just means that at the end of processing this message (SetCostOfCoffee
or GetCostOfCoffee
), the CoffeeMachine remains in the same State, which is Open
in our case.
The goto
, on the other hand transitions to a different State. We’ll see how it is done while discussing the Deposit
message.
Not surprisingly, check out the implementation of the stay
function
final def stay(): State = goto(currentState.stateName)
using
As you might already guessed, the using
function allows us to pass modified data to the next state. In case of the SetCostOfCoffee
message, we set the costOfCoffee
field of the MachineData
to the incoming price
wrapped inside the SetCostOfCoffee
. Since State is a case class (immutability is strongly advised unless you have fun debugging at odd hours), we do a copy
.
stateData
The stateData
is just a function that gives us a handle to the data of the FSM, which is the MachineData
itself. So, the following blocks of code are equivalent
case Event(GetCostOfCoffee, _) => sender ! (stateData.costOfCoffee); stay()
case Event(GetCostOfCoffee, machineData) => sender ! (machineData.costOfCoffee); stay()
The implementation of the maximum number of coffees to be dispensed using GetNumberOfCoffee
and SetNumberOfCoffee
is almost the same as the setting and getting the price itself. Let’s skip that and go for the interesting part – Buying coffee.
Buying coffee
So, the coffee enthusiast deposits money for the coffee but we can’t allow the machine to dispense coffee until he has entered the cost of a coffee. Also, if he has given extra cash, we’ll have to give him the balance. So, the various cases goes like this :
- Until the User deposits money to cover a coffee, we’ll keep track of the cumulative amount he has deposited and
stay
in theOpen
state. - Once the cumulative cash exceeds the price of a coffee, we’ll transition to the
ReadyToBuy
state and allow him to buy coffee. - At this
ReadyToBuy
state, he could change his mind andCancel
the transaction during which all his cumulativeBalance
is returned. - If he wishes to drink the coffee, he sends the machine a
BrewCoffee
message instead during which we dispense the coffee and give him back theBalance
money as well. (Actually, in our code, we don’t dispense the coffee. We just subtract the price of the coffee from his deposit and give him the balance. Such a rip off !!)
Let’s take each of the above cases
Case 1 – User deposits cash but falls short of the price of a coffee
Testcase
The testcase starts by setting the cost of the coffee to the $5 and the total number of coffees in the machine to be 10. We then Deposit $2 which is less than the price of the coffee and check if the Machine is in the Open
state and the total number of coffees in the machine remains at 10.
it("should stay at Transacting when the Deposit is less then the price of the coffee") { val coffeeMachine = TestActorRef(Props(new CoffeeMachine())) coffeeMachine ! SetCostOfCoffee(5) coffeeMachine ! SetNumberOfCoffee(10) coffeeMachine ! SubscribeTransitionCallBack(testActor) expectMsg(CurrentState(coffeeMachine, Open)) coffeeMachine ! Deposit(2) coffeeMachine ! GetNumberOfCoffee expectMsg(10) }
So, how exactly did we ensure that the machine is in the Open
state?
Each FSM can handle a special message called FSM.SubscribeTransitionCallBack(callerActorRef)
which enables the caller to be notified of any State transitions. The first notification that gets sent on subscription is the CurrentState
, which tells us what State the FSM is currently in. This is followed by several Transition
messages when that happens.
Implementation
So, we add up deposit to the cumulative transaction total and stay in Open
state waiting for more Deposit
when(Open) { ... ... case Event(Deposit(value), MachineData(currentTxTotal, costOfCoffee, coffeesLeft)) if (value + currentTxTotal) < stateData.costOfCoffee => { val cumulativeValue = currentTxTotal + value stay using stateData.copy(currentTxTotal = cumulativeValue) }
Case 2 and 4 – User deposits amount that covers the price of coffee
Testcase 1 – Deposit equal to the price of coffee
Our testcase bootstraps the machine, confirms if the current state is Open
and then deposits $5 which is exactly the price of the coffee. We then assert that the machine has transitioned from Open
to ReadyToBuy
by way of expecting a Transition
message which gives us information about the from and the to states of the coffee machine. In the first case, it is the transition from Open
to ReadyToBuy
.
We then go further and ask the machine to BrewCoffee
during which we expect a transition again from ReadyToBuy
to Open
upon dispensing the coffee. Finally an assertion is made against the remaining number of coffees in the machine (which is 9 now).
it("should transition to ReadyToBuy and then Open when the Deposit is equal to the price of the coffee") { val coffeeMachine = TestActorRef(Props(new CoffeeMachine())) coffeeMachine ! SetCostOfCoffee(5) coffeeMachine ! SetNumberOfCoffee(10) coffeeMachine ! SubscribeTransitionCallBack(testActor) expectMsg(CurrentState(coffeeMachine, Open)) coffeeMachine ! Deposit(5) expectMsg(Transition(coffeeMachine, Open, ReadyToBuy)) coffeeMachine ! BrewCoffee expectMsg(Transition(coffeeMachine, ReadyToBuy, Open)) coffeeMachine ! GetNumberOfCoffee expectMsg(9) }
Testcase 2 – Deposit greater than the price of the coffee
The second test case is 90% similar to the first testcase except that we deposit cash in increments that is greater than the price of the coffee ($6). Since we set the price of coffee to be $5, we now expect a Balance
message with value $1
it("should transition to ReadyToBuy and then Open when the Deposit is greater than the price of the coffee") { val coffeeMachine = TestActorRef(Props(new CoffeeMachine())) coffeeMachine ! SetCostOfCoffee(5) coffeeMachine ! SetNumberOfCoffee(10) coffeeMachine ! SubscribeTransitionCallBack(testActor) expectMsg(CurrentState(coffeeMachine, Open)) coffeeMachine ! Deposit(2) coffeeMachine ! Deposit(2) coffeeMachine ! Deposit(2) expectMsg(Transition(coffeeMachine, Open, ReadyToBuy)) coffeeMachine ! BrewCoffee expectMsgPF(){ case Balance(value)=>value==1 } expectMsg(Transition(coffeeMachine, ReadyToBuy, Open)) coffeeMachine ! GetNumberOfCoffee expectMsg(9) }
Implementation
The implementation is much simpler than the test cases itself. If the deposit amount is greater than or equal to the cost of coffee, then we goto
ReadyToBuy
state using the accumulated amount.
when(Open){ ... ... case Event(Deposit(value), MachineData(currentTxTotal, costOfCoffee, coffeesLeft)) if (value + currentTxTotal) >= stateData.costOfCoffee => { goto(ReadyToBuy) using stateData.copy(currentTxTotal = currentTxTotal + value) }
Once transitioned to the ReadyToBuy
state, when the user sends a BrewCoffee
, we check if there is a balance to be dispensed. If not, we just transition to Open
state after subtracting one coffee from the total number of coffees. Else, we disburse the balance and transition to Open
state after subtracting the number of coffees. (Like I said earlier, we don’t actually dispense coffee in this example)
when(ReadyToBuy) { case Event(BrewCoffee, MachineData(currentTxTotal, costOfCoffee, coffeesLeft)) => { val balanceToBeDispensed = currentTxTotal - costOfCoffee logger.debug(s"Balance is $balanceToBeDispensed") if (balanceToBeDispensed > 0) { sender ! Balance(value = balanceToBeDispensed) goto(Open) using stateData.copy(currentTxTotal = 0, coffeesLeft = coffeesLeft - 1) } else goto(Open) using stateData.copy(currentTxTotal = 0, coffeesLeft = coffeesLeft - 1) } }
That’s it !! We’ve covered the juice of the program.
Case 3 – User wishes to Cancel the transaction
Actually, the User should be in a position to Cancel
the transaction at any point, whatever state he is in. Like we discussed in Part 1, the perfect place to hold these kind of generic messages is in the whenUnhandled
block. We should also make sure that if the user has deposited some cash before canceling, we should give it back to them.
Implementation
whenUnhandled { ... ... case Event(Cancel, MachineData(currentTxTotal, _, _)) => { sender ! Balance(value = currentTxTotal) goto(Open) using stateData.copy(currentTxTotal = 0) } }
Testcase
The testcase is simply the same as the one we saw above except that the balance issued upon cancellation is the cumulative deposit.
it("should transition to Open after flushing out all the deposit when the coffee is canceled") { val coffeeMachine = TestActorRef(Props(new CoffeeMachine())) coffeeMachine ! SetCostOfCoffee(5) coffeeMachine ! SetNumberOfCoffee(10) coffeeMachine ! SubscribeTransitionCallBack(testActor) expectMsg(CurrentState(coffeeMachine, Open)) coffeeMachine ! Deposit(2) coffeeMachine ! Deposit(2) coffeeMachine ! Deposit(2) expectMsg(Transition(coffeeMachine, Open, ReadyToBuy)) coffeeMachine ! Cancel expectMsgPF(){ case Balance(value)=>value==6 } expectMsg(Transition(coffeeMachine, ReadyToBuy, Open)) coffeeMachine ! GetNumberOfCoffee expectMsg(10) }
Code
I didn’t want to bore you to death and took the liberty of skipping the explanation for ShutDownMachine
message and the PoweredOff
state but if you are looking forward to an explanation for them, please leave a comment.
As always, the code is available on github.
Reference: | Akka Notes – Finite State Machines – 2 from our JCG partner Arun Manivannan at the Rerun.me blog. |