# PartialFunction

trait PartialFunction[-A, +B] extends A => B

A partial function of type `PartialFunction[A, B]` is a unary function where the domain does not necessarily include all values of type `A`. The function isDefinedAt allows to test dynamically if a value is in the domain of the function.

Even if `isDefinedAt` returns true for an `a: A`, calling `apply(a)` may still throw an exception, so the following code is legal:

``val f: PartialFunction[Int, Any] = { case x => x / 0 }   // ArithmeticException: / by zero``

It is the responsibility of the caller to call `isDefinedAt` before calling `apply`, because if `isDefinedAt` is false, it is not guaranteed `apply` will throw an exception to indicate an error condition. If an exception is not thrown, evaluation may result in an arbitrary value.

The usual way to respect this contract is to call applyOrElse, which is expected to be more efficient than calling both `isDefinedAt` and `apply`.

The main distinction between `PartialFunction` and scala.Function1 is that the user of a `PartialFunction` may choose to do something different with input that is declared to be outside its domain. For example:

``````val sample = 1 to 10
def isEven(n: Int) = n % 2 == 0
val eveningNews: PartialFunction[Int, String] = {
case x if isEven(x) => s"\$x is even"
}

// The method collect is described as "filter + map"
// because it uses a PartialFunction to select elements
// to which the function is applied.
val evenNumbers = sample.collect(eveningNews)

val oddlyEnough: PartialFunction[Int, String] = {
case x if !isEven(x) => s"\$x is odd"
}

// The method orElse allows chaining another PartialFunction
// to handle input outside the declared domain.
val numbers = sample.map(eveningNews orElse oddlyEnough)

// same as
val numbers = sample.map(n => eveningNews.applyOrElse(n, oddlyEnough))

val half: PartialFunction[Int, Int] = {
case x if isEven(x) => x / 2
}

// Calculating the domain of a composition can be expensive.
val oddByHalf = half.andThen(oddlyEnough)

// Invokes `half.apply` on even elements!
val oddBalls = sample.filter(oddByHalf.isDefinedAt)

// Better than filter(oddByHalf.isDefinedAt).map(oddByHalf)
val oddBalls = sample.collect(oddByHalf)

// Providing "default" values.
val oddsAndEnds = sample.map(n => oddByHalf.applyOrElse(n, (i: Int) => s"[\$i]"))``````
Note:

Optional Functions, PartialFunctions and extractor objects can be converted to each other as shown in the following table.

How to convert ...

to a PartialFunction

to an optional Function

to an extractor

from a PartialFunction

from optional Function

from an extractor

`{ case extractor(x) => x }`

`extractor.unapply _`

Companion:
object
Source:
PartialFunction.scala
trait A => B
class Object
trait Matchable
class Any
trait MapOps[K, V, CC, C]
trait Map[K, V]
class AbstractMap[K, V]
class AbstractMap[K, V]
class HashMap[K, V]
class IntMap[T]
class ListMap[K, V]
class LongMap[T]
class Map1[K, V]
class Map2[K, V]
class Map3[K, V]
class Map4[K, V]
class WithDefault[K, V]
class WithDefault[K, V]
class TreeMap[K, V]
class TreeSeqMap[K, V]
class VectorMap[K, V]
class AbstractMap[K, V]
class TrieMap[K, V]
class AnyRefMap[K, V]
class HashMap[K, V]
class ListMap[K, V]
class LongMap[V]
class WithDefault[K, V]
class WithDefault[K, V]
class OpenHashMap[Key, Value]
class TreeMap[K, V]
trait DefaultMap[K, V]
trait SeqMap[K, V]
trait SeqMap[K, V]
trait SeqMap[K, V]
trait SortedMap[K, V]
trait SortedMap[K, V]
trait SortedMap[K, V]
trait Map[K, V]
trait Map[K, V]
trait Map[K, V]
trait MultiMap[K, V]
trait MapFactoryDefaults[K, V, CC, WithFilterCC]
class WeakHashMap[K, V]
trait MapView[K, V]
class AbstractMapView[K, V]
class Filter[K, V]
class FilterKeys[K, V]
class Id[K, V]
class MapValues[K, V, W]
class TapEach[K, V, U]
trait SortedMapFactoryDefaults[K, V, CC, WithFilterCC, UnsortedCC]
trait SortedMapOps[K, V, CC, C]
trait StrictOptimizedSortedMapOps[K, V, CC, C]
trait StrictOptimizedSortedMapOps[K, V, CC, C]
trait SortedMapOps[K, V, CC, C]
trait SortedMapOps[K, V, CC, C]
trait StrictOptimizedMapOps[K, V, CC, C]
trait StrictOptimizedMapOps[K, V, CC, C]
trait MapOps[K, V, CC, C]
trait MapOps[K, V, CC, C]
trait Seq[A]
class AbstractSeq[A]
class AbstractSeq[A]
class ArraySeq[A]
class ofBoolean
class ofByte
class ofChar
class ofDouble
class ofFloat
class ofInt
class ofLong
class ofRef[T]
class ofShort
class ofUnit
class LazyList[A]
class List[A]
class ::[A]
object Nil.type
class NumericRange[T]
class Exclusive[T]
class Inclusive[T]
class Queue[A]
class Range
class Exclusive
class Inclusive
class Stream[A]
class Cons[A]
object Empty.type
class Vector[A]
class AbstractSeq[A]
class ArrayBuffer[A]
class ArrayDeque[A]
class Queue[A]
class Stack[A]
class ListBuffer[A]
class ArraySeq[T]
class ofBoolean
class ofByte
class ofChar
class ofDouble
class ofFloat
class ofInt
class ofLong
class ofRef[T]
class ofShort
class ofUnit
trait IndexedSeq[A]
trait IndexedSeq[A]
trait IndexedSeq[T]
trait IndexedBuffer[A]
trait LinearSeq[A]
trait LinearSeq[A]
trait Seq[A]
trait Seq[A]
trait Buffer[A]
class Accumulator[A, CC, C]

## Value members

### Abstract methods

def isDefinedAt(x: A): Boolean

Checks if a value is contained in the function's domain.

Checks if a value is contained in the function's domain.

Value parameters:
x

the value to test

Returns:

`true`, iff `x` is in the domain of this function, `false` otherwise.

Source:
PartialFunction.scala

### Concrete methods

override def andThen[C](k: B => C): PartialFunction[A, C]

Composes this partial function with a transformation function that gets applied to results of this partial function.

Composes this partial function with a transformation function that gets applied to results of this partial function.

If the runtime type of the function is a `PartialFunction` then the other `andThen` method is used (note its cautions).

Type parameters:
C

the result type of the transformation function.

Value parameters:
k

the transformation function

Returns:

a partial function with the domain of this partial function, possibly narrowed by the specified function, which maps arguments `x` to `k(this(x))`.

Definition Classes
Source:
PartialFunction.scala
def andThen[C](k: PartialFunction[B, C]): PartialFunction[A, C]

Composes this partial function with another partial function that gets applied to results of this partial function.

Composes this partial function with another partial function that gets applied to results of this partial function.

Note that calling isDefinedAt on the resulting partial function may apply the first partial function and execute its side effect. For efficiency, it is recommended to call applyOrElse instead of isDefinedAt or apply.

Type parameters:
C

the result type of the transformation function.

Value parameters:
k

the transformation function

Returns:

a partial function with the domain of this partial function narrowed by other partial function, which maps arguments `x` to `k(this(x))`.

Source:
PartialFunction.scala
def applyOrElse[A1 <: A, B1 >: B](x: A1, default: A1 => B1): B1

Applies this partial function to the given argument when it is contained in the function domain.

Applies this partial function to the given argument when it is contained in the function domain. Applies fallback function where this partial function is not defined.

Note that expression `pf.applyOrElse(x, default)` is equivalent to

``if(pf isDefinedAt x) pf(x) else default(x)``

except that `applyOrElse` method can be implemented more efficiently. For all partial function literals the compiler generates an `applyOrElse` implementation which avoids double evaluation of pattern matchers and guards. This makes `applyOrElse` the basis for the efficient implementation for many operations and scenarios, such as:

- combining partial functions into `orElse`/`andThen` chains does not lead to excessive `apply`/`isDefinedAt` evaluation - `lift` and `unlift` do not evaluate source functions twice on each invocation - `runWith` allows efficient imperative-style combining of partial functions with conditionally applied actions

For non-literal partial function classes with nontrivial `isDefinedAt` method it is recommended to override `applyOrElse` with custom implementation that avoids double `isDefinedAt` evaluation. This may result in better performance and more predictable behavior w.r.t. side effects.

Value parameters:
default

the fallback function

x

the function argument

Returns:

the result of this function or fallback function application.

Source:
PartialFunction.scala
def compose[R](k: PartialFunction[R, A]): PartialFunction[R, B]

Composes another partial function `k` with this partial function so that this partial function gets applied to results of `k`.

Composes another partial function `k` with this partial function so that this partial function gets applied to results of `k`.

Note that calling isDefinedAt on the resulting partial function may apply the first partial function and execute its side effect. For efficiency, it is recommended to call applyOrElse instead of isDefinedAt or apply.

Type parameters:
R

the parameter type of the transformation function.

Value parameters:
k

the transformation function

Returns:

a partial function with the domain of other partial function narrowed by this partial function, which maps arguments `x` to `this(k(x))`.

Source:
PartialFunction.scala

Returns an extractor object with a `unapplySeq` method, which extracts each element of a sequence data.

Returns an extractor object with a `unapplySeq` method, which extracts each element of a sequence data.

Example:

``````val firstChar: String => Option[Char] = _.headOption
Seq("foo", "bar", "baz") match {
case firstChar.unlift.elementWise(c0, c1, c2) =>
println(s"\$c0, \$c1, \$c2") // Output: f, b, b
}``````
Source:
PartialFunction.scala
def lift: A => Option[B]

Turns this partial function into a plain function returning an `Option` result.

Turns this partial function into a plain function returning an `Option` result.

Returns:

a function that takes an argument `x` to `Some(this(x))` if `this` is defined for `x`, and to `None` otherwise.

Function.unlift

Source:
PartialFunction.scala
def orElse[A1 <: A, B1 >: B](that: PartialFunction[A1, B1]): PartialFunction[A1, B1]

Composes this partial function with a fallback partial function which gets applied where this partial function is not defined.

Composes this partial function with a fallback partial function which gets applied where this partial function is not defined.

Type parameters:
A1

the argument type of the fallback function

B1

the result type of the fallback function

Value parameters:
that

the fallback function

Returns:

a partial function which has as domain the union of the domains of this partial function and `that`. The resulting partial function takes `x` to `this(x)` where `this` is defined, and to `that(x)` where it is not.

Source:
PartialFunction.scala
def runWith[U](action: B => U): A => Boolean

Composes this partial function with an action function which gets applied to results of this partial function.

Composes this partial function with an action function which gets applied to results of this partial function. The action function is invoked only for its side effects; its result is ignored.

Note that expression `pf.runWith(action)(x)` is equivalent to

``if(pf isDefinedAt x) { action(pf(x)); true } else false``

except that `runWith` is implemented via `applyOrElse` and thus potentially more efficient. Using `runWith` avoids double evaluation of pattern matchers and guards for partial function literals.

Value parameters:
action

the action function

Returns:

a function which maps arguments `x` to `isDefinedAt(x)`. The resulting function runs `action(this(x))` where `this` is defined.

`applyOrElse`.

Source:
PartialFunction.scala
def unapply(a: A): Option[B]

Tries to extract a `B` from an `A` in a pattern matching expression.

Tries to extract a `B` from an `A` in a pattern matching expression.

Source:
PartialFunction.scala

### Inherited methods

def apply(v1: A): B

Apply the body of this function to the argument.

Apply the body of this function to the argument.

Returns:

the result of function application.

Inherited from:
Function1
Source:
Function1.scala
def compose[A](g: A => A): A => B

Composes two instances of Function1 in a new Function1, with this function applied last.

Composes two instances of Function1 in a new Function1, with this function applied last.

Type parameters:
A

the type to which function `g` can be applied

Value parameters:
g

a function A => T1

Returns:

a new function `f` such that `f(x) == apply(g(x))`

Inherited from:
Function1
Source:
Function1.scala
override def toString(): String
Definition Classes
Inherited from:
Function1
Source:
Function1.scala