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+---
+layout: docs
+title:  "ContT"
+section: "data"
+source: "core/src/main/scala/cats/data/ContT.scala"
+scaladoc: "#cats.data.ContT"
+---
+# 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:
+
+```tut:silent
+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
+```
+
+```tut:book
+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](eval.html) 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:
+
+```tut:book
+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:
+
+```tut:book
+val existingUser = User(100, "Alice", 42)
+
+val computation = updateUserCont(existingUser, "Bob", 200)
+```
+
+And then call `run` on it, passing in a function of type `User =>
+Eval[UserUpdateResult]` as the continuation:
+
+```tut:book
+val eval = computation.run { user =>
+  Eval.later {
+    println(s"Persisting updated user to the DB: $user")
+    Succeeded(user.id)
+  }
+}
+```
+
+Finally we can run the resulting `Eval` to actually execute the computation:
+
+```tut:book
+eval.value
+```
+
+## 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`:
+
+```tut:book
+val anotherComputation = computation.map { user =>
+  Map(
+    "id" -> user.id.toString,
+    "name" -> user.name,
+    "age" -> user.age.toString
+  )
+}
+
+val anotherEval = anotherComputation.run { userFields =>
+  Eval.later {
+    println(s"Persisting these fields to the DB: $userFields")
+    Succeeded(userFields("id").toInt)
+  }
+}
+
+anotherEval.value
+```
+
+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.
+
+```tut:book
+val updateUserModel: ContT[Eval, UserUpdateResult, User] =
+  updateUserCont(existingUser, "Bob", 200).map { updatedUser =>
+    println("Updated user model")
+    updatedUser
+  }
+
+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))
+    }
+}
+
+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)
+    }
+}
+
+val chainOfContinuations =
+  updateUserModel flatMap persistToDb flatMap publishEvent
+
+val eval = chainOfContinuations.run { finalResult =>
+  Eval.later {
+    println("Finished!")
+    finalResult
+  }
+}
+
+eval.value
+```
+
+## 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.