scala.util

DynamicVariables provide a binding mechanism where the current value is found through dynamic scope, but where access to the variable itself is resolved through static scope.

The current value can be retrieved with the value method. New values should be pushed using the withValue method. Values pushed via withValue only stay valid while the withValue's second argument, a parameterless closure, executes. When the second argument finishes, the variable reverts to the previous value.

someDynamicVariable.withValue(newValue) {
  // ... code called in here that calls value ...
  // ... will be given back the newValue ...
}

Each thread gets its own stack of bindings. When a new thread is created, the DynamicVariable gets a copy of the stack of bindings from the parent thread, and from then on the bindings for the new thread are independent of those for the original thread.

Represents a value of one of two possible types (a disjoint union). An instance of Either is an instance of either scala.util.Left or scala.util.Right.

A common use of Either is as an alternative to scala.Option for dealing with possibly missing values. In this usage, scala.None is replaced with a scala.util.Left which can contain useful information. scala.util.Right takes the place of scala.Some. Convention dictates that Left is used for failure and Right is used for success.

For example, you could use Either[String, Int] to indicate whether a received input is a String or an Int.

import scala.io.StdIn._
val in = readLine("Type Either a string or an Int: ")
val result: Either[String,Int] =
  try Right(in.toInt)
  catch {
    case e: NumberFormatException => Left(in)
  }

result match {
  case Right(x) => s"You passed me the Int: $x, which I will increment. $x + 1 = ${x+1}"
  case Left(x)  => s"You passed me the String: $x"
}

Either is right-biased, which means that Right is assumed to be the default case to operate on. If it is Left, operations like map and flatMap return the Left value unchanged:

def doubled(i: Int) = i * 2
Right(42).map(doubled) // Right(84)
Left(42).map(doubled)  // Left(42)

Since Either defines the methods map and flatMap, it can also be used in for comprehensions:

val right1 = Right(1)   : Right[Double, Int]
val right2 = Right(2)
val right3 = Right(3)
val left23 = Left(23.0) : Left[Double, Int]
val left42 = Left(42.0)

for {
  x <- right1
  y <- right2
  z <- right3
} yield x + y + z // Right(6)

for {
  x <- right1
  y <- right2
  z <- left23
} yield x + y + z // Left(23.0)

for {
  x <- right1
  y <- left23
  z <- right2
} yield x + y + z // Left(23.0)

// Guard expressions are not supported:
for {
  i <- right1
  if i > 0
} yield i
// error: value withFilter is not a member of Right[Double,Int]

// Similarly, refutable patterns are not supported:
for (x: Int <- right1) yield x
// error: value withFilter is not a member of Right[Double,Int]

Since for comprehensions use map and flatMap, the types of function parameters used in the expression must be inferred. These types are constrained by the Either values. In particular, because of right-biasing, Left values may require an explicit type argument for type parameter B, the right value. Otherwise, it might be inferred as Nothing.

for {
  x <- left23
  y <- right1
  z <- left42  // type at this position: Either[Double, Nothing]
} yield x + y + z
//            ^
// error: ambiguous reference to overloaded definition,
// both method + in class Int of type (x: Char)Int
// and  method + in class Int of type (x: Byte)Int
// match argument types (Nothing)

for (x <- right2 ; y <- left23) yield x + y  // Left(23.0)
for (x <- right2 ; y <- left42) yield x + y  // error

for {
  x <- right1
  y <- left42  // type at this position: Either[Double, Nothing]
  z <- left23
} yield x + y + z
// Left(42.0), but unexpectedly a `Either[Double,String]`

A special class used to implement negation in implicit search.

Consider the problem of using implicit i1 for a query type D if an implicit for some other class C is available, and using an implicit i2 if no implicit value of type C is available. If we do not want to prioritize i1 and i2 by putting them in different traits we can instead define the following:

given i1: D(using ev: C) = ... given i2: D(using ev: NotGiven[C]) = ...

NotGiven is treated specially in implicit search, similar to the way logical negation is treated in Prolog: The implicit search for NotGiven[C] succeeds if and only if the implicit search for C fails.

In Scala 2 this form of negation can be simulated by setting up a conditional ambiguous implicit and an unconditional fallback, the way it is done with the default, amb1 and amb2 methods below. Due to the way these two methods are defined, NotGiven is also usable from Scala 2.

In Dotty, ambiguity is a global error, and therefore cannot be used to implement negation. Instead, NotGiven is treated natively in implicit search.

The Sorting object provides convenience wrappers for java.util.Arrays.sort. Methods that defer to java.util.Arrays.sort say that they do or under what conditions that they do.

Sorting also implements a general-purpose quicksort and stable (merge) sort for those cases where java.util.Arrays.sort could only be used at the cost of a large memory penalty. If performance rather than memory usage is the primary concern, one may wish to find alternate strategies to use java.util.Arrays.sort directly e.g. by boxing primitives to use a custom ordering on them.

Sorting provides methods where you can provide a comparison function, or can request a sort of items that are scala.math.Ordered or that otherwise have an implicit or explicit scala.math.Ordering.

Note also that high-performance non-default sorts for numeric types are not provided. If this is required, it is advisable to investigate other libraries that cover this use case.

The Try type represents a computation that may either result in an exception, or return a successfully computed value. It's similar to, but semantically different from the scala.util.Either type.

Instances of Try[T], are either an instance of scala.util.Success[T] or scala.util.Failure[T].

For example, Try can be used to perform division on a user-defined input, without the need to do explicit exception-handling in all of the places that an exception might occur.

Example:

import scala.io.StdIn
import scala.util.{Try, Success, Failure}

def divide: Try[Int] = {
  val dividend = Try(StdIn.readLine("Enter an Int that you'd like to divide:\n").toInt)
  val divisor = Try(StdIn.readLine("Enter an Int that you'd like to divide by:\n").toInt)
  val problem = dividend.flatMap(x => divisor.map(y => x/y))
  problem match {
    case Success(v) =>
      println("Result of " + dividend.get + "/"+ divisor.get +" is: " + v)
      Success(v)
    case Failure(e) =>
      println("You must've divided by zero or entered something that's not an Int. Try again!")
      println("Info from the exception: " + e.getMessage)
      divide
  }
}

An important property of Try shown in the above example is its ability to pipeline, or chain, operations, catching exceptions along the way. The flatMap and map combinators in the above example each essentially pass off either their successfully completed value, wrapped in the Success type for it to be further operated upon by the next combinator in the chain, or the exception wrapped in the Failure type usually to be simply passed on down the chain. Combinators such as recover and recoverWith are designed to provide some type of default behavior in the case of failure.

Note: only non-fatal exceptions are caught by the combinators on Try (see scala.util.control.NonFatal). Serious system errors, on the other hand, will be thrown.

Note:: all Try combinators will catch exceptions and return failure unless otherwise specified in the documentation.

Try comes to the Scala standard library after years of use as an integral part of Twitter's stack.

A utility for performing automatic resource management. It can be used to perform an operation using resources, after which it releases the resources in reverse order of their creation.

Usage

There are multiple ways to automatically manage resources with Using. If you only need to manage a single resource, the apply method is easiest; it wraps the resource opening, operation, and resource releasing in a Try.

Example:

import java.io.{BufferedReader, FileReader}
import scala.util.{Try, Using}

val lines: Try[Seq[String]] =
 Using(new BufferedReader(new FileReader("file.txt"))) { reader =>
   Iterator.continually(reader.readLine()).takeWhile(_ != null).toSeq
 }

If you need to manage multiple resources, Using.Manager should be used. It allows the managing of arbitrarily many resources, whose creation, use, and release are all wrapped in a Try.

Example:

import java.io.{BufferedReader, FileReader}
import scala.util.{Try, Using}

val lines: Try[Seq[String]] = Using.Manager { use =>
 val r1 = use(new BufferedReader(new FileReader("file1.txt")))
 val r2 = use(new BufferedReader(new FileReader("file2.txt")))
 val r3 = use(new BufferedReader(new FileReader("file3.txt")))
 val r4 = use(new BufferedReader(new FileReader("file4.txt")))

 // use your resources here
 def lines(reader: BufferedReader): Iterator[String] =
   Iterator.continually(reader.readLine()).takeWhile(_ != null)

 (lines(r1) ++ lines(r2) ++ lines(r3) ++ lines(r4)).toList
}

If you wish to avoid wrapping management and operations in a Try, you can use Using.resource, which throws any exceptions that occur.

Example:

import java.io.{BufferedReader, FileReader}
import scala.util.Using

val lines: Seq[String] =
 Using.resource(new BufferedReader(new FileReader("file.txt"))) { reader =>
   Iterator.continually(reader.readLine()).takeWhile(_ != null).toSeq
 }

Suppression Behavior

If two exceptions are thrown (e.g., by an operation and closing a resource), one of them is re-thrown, and the other is added to it as a suppressed exception. If the two exceptions are of different 'severities' (see below), the one of a higher severity is re-thrown, and the one of a lower severity is added to it as a suppressed exception. If the two exceptions are of the same severity, the one thrown first is re-thrown, and the one thrown second is added to it as a suppressed exception. If an exception is a ControlThrowable, or if it does not support suppression (see Throwable's constructor with an enableSuppression parameter), an exception that would have been suppressed is instead discarded.

Exceptions are ranked from highest to lowest severity as follows:

• java.lang.VirtualMachineError

• java.lang.LinkageError

• java.lang.InterruptedException and java.lang.ThreadDeath

• fatal exceptions, excluding scala.util.control.ControlThrowable

• scala.util.control.ControlThrowable

• all other exceptions

When more than two exceptions are thrown, the first two are combined and re-thrown as described above, and each successive exception thrown is combined as it is thrown.