ContT
API Documentation: ContT
A pattern that appears sometimes in functional programming is that of a function first computing some kind of intermediate result and then passing that result to another function which was passed in as an argument, in order to delegate the computation of the final result.
For example:
case class User(id: Int, name: String, age: Int)
sealed abstract class UserUpdateResult
case class Succeeded(updatedUserId: Int) extends UserUpdateResult
case object Failed extends UserUpdateResult
import cats.Eval
def updateUser(persistToDatabase: User => Eval[UserUpdateResult])
(existingUser: User, newName: String, newAge: Int): Eval[UserUpdateResult] = {
val trimmedName = newName.trim
val cappedAge = newAge max 150
val updatedUser = existingUser.copy(name = trimmedName, age = cappedAge)
persistToDatabase(updatedUser)
}
(Note: We will be using Eval
throughout the examples on this page. If you are not
familiar with Eval
, it's worth reading the Eval documentation first.)
Our updateUser
function takes in an existing user and some updates to perform.
It sanitises the inputs and updates the user model, but it delegates the
database update to another function which is passed in as an argument.
This pattern is known as "continuation passing style" or CPS, and the function
passed in (persistToDatabase
) is known as a "continuation".
Note the following characteristics:
- The return type of our
updateUser
function (Eval[UserUpdateResult]
) is the same as the return type of the continuation function that was passed in. - Our function does a bit of work to build an intermediate value, then passes that value to the continuation, which takes care of the remainder of the work.
In Cats we can encode this pattern using the ContT
data type:
import cats.data.ContT
def updateUserCont(existingUser: User,
newName: String,
newAge: Int): ContT[Eval, UserUpdateResult, User] =
ContT.apply[Eval, UserUpdateResult, User] { next =>
val trimmedName = newName.trim
val cappedAge = newAge min 150
val updatedUser = existingUser.copy(name = trimmedName, age = cappedAge)
next(updatedUser)
}
We can construct a computation as follows:
val existingUser = User(100, "Alice", 42)
// existingUser: User = User(id = 100, name = "Alice", age = 42)
val computation = updateUserCont(existingUser, "Bob", 200)
// computation: ContT[Eval, UserUpdateResult, User] = FromFn(
// runAndThen = Single(f = <function1>, index = 0)
// )
And then call run
on it, passing in a function of type User =>
Eval[UserUpdateResult]
as the continuation:
val eval = computation.run { user =>
Eval.later {
println(s"Persisting updated user to the DB: $user")
Succeeded(user.id)
}
}
// eval: Eval[UserUpdateResult] = cats.Later@68edb6dd
Finally we can run the resulting Eval
to actually execute the computation:
eval.value
// Persisting updated user to the DB: User(100,Bob,150)
// res0: UserUpdateResult = Succeeded(updatedUserId = 100)
Composition
You might be wondering what the point of all this was, as the function that uses
ContT
seems to achieve the same thing as the original function, just encoded
in a slightly different way.
The point is that ContT
is a monad, so by rewriting our function into a
ContT
we gain composibility for free.
For example we can map
over a ContT
:
val anotherComputation = computation.map { user =>
Map(
"id" -> user.id.toString,
"name" -> user.name,
"age" -> user.age.toString
)
}
// anotherComputation: ContT[Eval, UserUpdateResult, Map[String, String]] = FromFn(
// runAndThen = Single(
// f = cats.data.ContT$$Lambda$14430/0x00007f6330685398@32a2b5ea,
// index = 0
// )
// )
val anotherEval = anotherComputation.run { userFields =>
Eval.later {
println(s"Persisting these fields to the DB: $userFields")
Succeeded(userFields("id").toInt)
}
}
// anotherEval: Eval[UserUpdateResult] = cats.Eval$$anon$5@6435b180
anotherEval.value
// Persisting these fields to the DB: Map(id -> 100, name -> Bob, age -> 150)
// res1: UserUpdateResult = Succeeded(updatedUserId = 100)
And we can use flatMap
to chain multiple ContT
s together.
The following example builds 3 computations: one to sanitise the inputs and
update the user model, one to persist the updated user to the database, and one
to publish a message saying the user was updated. It then chains them together
in continuation-passing style using flatMap
and runs the whole computation.
val updateUserModel: ContT[Eval, UserUpdateResult, User] =
updateUserCont(existingUser, "Bob", 200).map { updatedUser =>
println("Updated user model")
updatedUser
}
// updateUserModel: ContT[Eval, UserUpdateResult, User] = FromFn(
// runAndThen = Single(
// f = cats.data.ContT$$Lambda$14430/0x00007f6330685398@9a086f1,
// index = 0
// )
// )
val persistToDb: User => ContT[Eval, UserUpdateResult, UserUpdateResult] = {
user =>
ContT.apply[Eval, UserUpdateResult, UserUpdateResult] { next =>
println(s"Persisting updated user to the DB: $user")
next(Succeeded(user.id))
}
}
// persistToDb: User => ContT[Eval, UserUpdateResult, UserUpdateResult] = <function1>
val publishEvent: UserUpdateResult => ContT[Eval, UserUpdateResult, UserUpdateResult] = {
userUpdateResult =>
ContT.apply[Eval, UserUpdateResult, UserUpdateResult] { next =>
userUpdateResult match {
case Succeeded(userId) =>
println(s"Publishing 'user updated' event for user ID $userId")
case Failed =>
println("Not publishing 'user updated' event because update failed")
}
next(userUpdateResult)
}
}
// publishEvent: UserUpdateResult => ContT[Eval, UserUpdateResult, UserUpdateResult] = <function1>
val chainOfContinuations =
updateUserModel flatMap persistToDb flatMap publishEvent
// chainOfContinuations: ContT[Eval, UserUpdateResult, UserUpdateResult] = FromFn(
// runAndThen = Single(
// f = cats.data.ContT$$Lambda$14434/0x00007f6330685d20@6c75cdce,
// index = 0
// )
// )
val eval = chainOfContinuations.run { finalResult =>
Eval.later {
println("Finished!")
finalResult
}
}
// eval: Eval[UserUpdateResult] = cats.Eval$$anon$5@d9681f0
eval.value
// Updated user model
// Persisting updated user to the DB: User(100,Bob,150)
// Publishing 'user updated' event for user ID 100
// Finished!
// res2: UserUpdateResult = Succeeded(updatedUserId = 100)
Why Eval?
If you're wondering why we used Eval
in our examples above, it's because the
Monad
instance for ContT[M[_], A, B]
requires an instance of cats.Defer
for M[_]
. This is an implementation detail - it's needed in order to preserve
stack safety.
In a real-world application, you're more likely to be using something like
cats-effect IO
, which has a Defer
instance.