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See more training or add one to our feed. See more events or add one to our feed. With Scaladex, a developer can now query more than , releases of Scala libraries.
Scaladex is officially supported by Scala Center. Scala 2. For all the details, refer to the release notes on GitHub. Black Lives Matter.
Systemic racial discrimination and state-supported brutality is unacceptable. The Scala Center team further: we re For instance, the compiler can summon JSON serializers and des Scala runs on Scala in a Nutshell click the boxes below to see Scala in action!
Type inference. Let the compiler figure out the types for you The Scala compiler is smart about static types. Traits Combine the flexibility of Java-style interfaces with the power of classes.
Match against class hierarchies, sequences, and more. Higher-order functions Functions are first-class objects. Switch on the structure of your data In Scala, case classes are used to represent structural data types.
Pattern matching. Go Functional with Higher-Order Functions In Scala, functions are values, and can be defined as anonymous functions with a concise syntax.
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The following are some examples:. By themselves, these may seem like questionable choices, but collectively they serve the purpose of allowing domain-specific languages to be defined in Scala without needing to extend the compiler.
For example, Erlang 's special syntax for sending a message to an actor, i. Java makes a sharp distinction between primitive types e.
Only reference types are part of the inheritance scheme, deriving from java. In Scala, all types inherit from a top-level class Any , whose immediate children are AnyVal value types, such as Int and Boolean and AnyRef reference types, as in Java.
This means that the Java distinction between primitive types and boxed types e. Integer is not present in Scala; boxing and unboxing is completely transparent to the user.
Scala 2. Instead of the Java " foreach " loops for looping through an iterator, Scala has for -expressions, which are similar to list comprehensions in languages such as Haskell, or a combination of list comprehensions and generator expressions in Python.
For-expressions using the yield keyword allow a new collection to be generated by iterating over an existing one, returning a new collection of the same type.
They are translated by the compiler into a series of map , flatMap and filter calls. Where yield is not used, the code approximates to an imperative-style loop, by translating to foreach.
Note that the expression 1 to 25 is not special syntax. The method to is rather defined in the standard Scala library as an extension method on integers, using a technique known as implicit conversions  that allows new methods to be added to existing types.
Iterating over a map returns a set of key-value tuples , and pattern-matching allows the tuples to easily be destructured into separate variables for the key and value.
Similarly, the result of the comprehension also returns key-value tuples, which are automatically built back up into a map because the source object from the variable mentions is a map.
Note that if mentions instead held a list, set, array or other collection of tuples, exactly the same code above would yield a new collection of the same type.
While supporting all of the object-oriented features available in Java and in fact, augmenting them in various ways , Scala also provides a large number of capabilities that are normally found only in functional programming languages.
Together, these features allow Scala programs to be written in an almost completely functional style and also allow functional and object-oriented styles to be mixed.
Unlike C or Java, but similar to languages such as Lisp , Scala makes no distinction between statements and expressions. All statements are in fact expressions that evaluate to some value.
Functions that would be declared as returning void in C or Java, and statements like while that logically do not return a value, are in Scala considered to return the type Unit , which is a singleton type , with only one object of that type.
Functions and operators that never return at all e. This in turn makes type Nothing compatible with every type, allowing type inference to function correctly.
Similarly, an if-then-else "statement" is actually an expression, which produces a value, i. This means that such a block of code can be inserted wherever an expression is desired, obviating the need for a ternary operator in Scala:.
For similar reasons, return statements are unnecessary in Scala, and in fact are discouraged. As in Lisp, the last expression in a block of code is the value of that block of code, and if the block of code is the body of a function, it will be returned by the function.
To make it clear that all functions are expressions, even methods that return Unit are written with an equals sign. Due to type inference , the type of variables, function return values, and many other expressions can typically be omitted, as the compiler can deduce it.
Type inference in Scala is essentially local, in contrast to the more global Hindley-Milner algorithm used in Haskell , ML and other more purely functional languages.
This is done to facilitate object-oriented programming. The result is that certain types still need to be declared most notably, function parameters, and the return types of recursive functions , e.
In Scala, functions are objects, and a convenient syntax exists for specifying anonymous functions. Note that neither the type of x nor the return type need be explicitly specified, and can generally be inferred by type inference ; but they can be explicitly specified, e.
Anonymous functions behave as true closures in that they automatically capture any variables that are lexically available in the environment of the enclosing function.
Those variables will be available even after the enclosing function returns, and unlike in the case of Java's anonymous inner classes do not need to be declared as final.
It is even possible to modify such variables if they are mutable, and the modified value will be available the next time the anonymous function is called.
An even shorter form of anonymous function uses placeholder variables: For example, the following:. Scala enforces a distinction between immutable and mutable variables.
Mutable variables are declared using the var keyword and immutable values are declared using the val keyword. A variable declared using the val keyword can not be reassigned in the same way that a variable declared using the final keyword can't be reassigned in Java.
It should be noted however that val 's are only shallowly immutable, that is, an object referenced by a val is not guaranteed to itself be immutable.
Immutable classes are encouraged by convention however, and the Scala standard library provides a rich set of immutable collection classes.
Scala provides mutable and immutable variants of most collection classes, and the immutable version is always used unless the mutable version is explicitly imported.
An example of this is immutable linked lists where prepending an element to a list is done by returning a new list node consisting of the element and a reference to the list tail.
Appending an element to a list can only be done by prepending all elements in the old list to a new list with only the new element.
In the same way, inserting an element in the middle of a list will copy the first half of the list, but keep a reference to the second half of the list.
This is called structural sharing. This allows for very easy concurrency — no locks are needed as no shared objects are ever modified.
Evaluation is strict "eager" by default. In other words, Scala evaluates expressions as soon as they are available, rather than as needed.
However, it is possible to declare a variable non-strict "lazy" with the lazy keyword, meaning that the code to produce the variable's value will not be evaluated until the first time the variable is referenced.
Non-strict collections of various types also exist such as the type Stream , a non-strict linked list , and any collection can be made non-strict with the view method.
Non-strict collections provide a good semantic fit to things like server-produced data, where the evaluation of the code to generate later elements of a list that in turn triggers a request to a server, possibly located somewhere else on the web only happens when the elements are actually needed.
Functional programming languages commonly provide tail call optimization to allow for extensive use of recursion without stack overflow problems.
Limitations in Java bytecode complicate tail call optimization on the JVM. In general, a function that calls itself with a tail call can be optimized, but mutually recursive functions cannot.
Trampolines have been suggested as a workaround. TailCalls since Scala 2. A function may optionally be annotated with tailrec , in which case it will not compile unless it is tail recursive.
Scala has built-in support for pattern matching , which can be thought of as a more sophisticated, extensible version of a switch statement , where arbitrary data types can be matched rather than just simple types like integers, booleans and strings , including arbitrary nesting.
A special type of class known as a case class is provided, which includes automatic support for pattern matching and can be used to model the algebraic data types used in many functional programming languages.
From the perspective of Scala, a case class is simply a normal class for which the compiler automatically adds certain behaviors that could also be provided manually, e.
An example of a definition of the quicksort algorithm using pattern matching is this:. The idea here is that we partition a list into the elements less than a pivot and the elements not less, recursively sort each part, and paste the results together with the pivot in between.
This uses the same divide-and-conquer strategy of mergesort and other fast sorting algorithms. The match operator is used to do pattern matching on the object stored in list.
Each case expression is tried in turn to see if it will match, and the first match determines the result.
In this case, the associated code will have access to a local variable named pivot holding the head of the list, and another variable tail holding the tail of the list.
Note that these variables are read-only, and are semantically very similar to variable bindings established using the let operator in Lisp and Scheme.
Pattern matching also happens in local variable declarations. In this case, the return value of the call to tail.
Tuples differ from other types of containers, e. Pattern matching is the easiest way of fetching the two parts of the tuple.
The list operators :: which adds an element onto the beginning of a list, similar to cons in Lisp and Scheme and which appends two lists together, similar to append in Lisp and Scheme both appear.
Despite appearances, there is nothing "built-in" about either of these operators. As specified above, any string of symbols can serve as function name, and a method applied to an object can be written " infix "-style without the period or parentheses.
The line above as written:. Methods that end with a colon are right-associative and bind to the object to the right.
In the pattern-matching example above, the body of the match operator is a partial function , which consists of a series of case expressions, with the first matching expression prevailing, similar to the body of a switch statement.
Partial functions are also used in the exception-handling portion of a try statement:. Finally, a partial function can be used alone, and the result of calling it is equivalent to doing a match over it.
For example, the prior code for quicksort can be written thus:. Here a read-only variable is declared whose type is a function from lists of integers to lists of integers, and bind it to a partial function.
Note that the single parameter of the partial function is never explicitly declared or named. However, we can still call this variable exactly as if it were a normal function:.
Scala is a pure object-oriented language in the sense that every value is an object. Data types and behaviors of objects are described by classes and traits.
Class abstractions are extended by subclassing and by a flexible mixin -based composition mechanism to avoid the problems of multiple inheritance.
Traits are Scala's replacement for Java's interfaces. Interfaces in Java versions under 8 are highly restricted, able only to contain abstract function declarations.
This has led to criticism that providing convenience methods in interfaces is awkward the same methods must be reimplemented in every implementation , and extending a published interface in a backwards-compatible way is impossible.
Traits are similar to mixin classes in that they have nearly all the power of a regular abstract class, lacking only class parameters Scala's equivalent to Java's constructor parameters , since traits are always mixed in with a class.
The super operator behaves specially in traits, allowing traits to be chained using composition in addition to inheritance.
The following example is a simple window system:. In other words, the call to draw first executed the code in TitleDecoration the last trait mixed in , then through the super calls threaded back through the other mixed-in traits and eventually to the code in Window , even though none of the traits inherited from one another.
This is similar to the decorator pattern , but is more concise and less error-prone, as it doesn't require explicitly encapsulating the parent window, explicitly forwarding functions whose implementation isn't changed, or relying on run-time initialization of entity relationships.
In other languages, a similar effect could be achieved at compile-time with a long linear chain of implementation inheritance , but with the disadvantage compared to Scala that one linear inheritance chain would have to be declared for each possible combination of the mix-ins.
Scala is equipped with an expressive static type system that mostly enforces the safe and coherent use of abstractions.
The type system is, however, not sound. Scala is able to infer types by usage. This makes most static type declarations optional. Static types need not be explicitly declared unless a compiler error indicates the need.
In practice, some static type declarations are included for the sake of code clarity. A common technique in Scala, known as "enrich my library"  originally termed as "pimp my library" by Martin Odersky in ;  though concerns were raised about this phrasing due to its negative connotation  and immaturity  , allows new methods to be used as if they were added to existing types.
This is similar to the C concept of extension methods but more powerful, because the technique is not limited to adding methods and can, for instance, be used to implement new interfaces.
In Scala, this technique involves declaring an implicit conversion from the type "receiving" the method to a new type typically, a class that wraps the original type and provides the additional method.
If a method cannot be found for a given type, the compiler automatically searches for any applicable implicit conversions to types that provide the method in question.
This technique allows new methods to be added to an existing class using an add-on library such that only code that imports the add-on library gets the new functionality, and all other code is unaffected.
The following example shows the enrichment of type Int with methods isEven and isOdd :. Importing the members of MyExtensions brings the implicit conversion to extension class IntPredicates into scope.
Scala's standard library includes support for the actor model , in addition to the standard Java concurrency APIs.
Lightbend Inc. Akka actors may be distributed or combined with software transactional memory transactors.
An Actor is like a thread instance with a mailbox. It can be created by system. Scala also comes with built-in support for data-parallel programming in the form of Parallel Collections  integrated into its Standard Library since version 2.
The following example shows how to use Parallel Collections to improve performance. Besides actor support and data-parallelism, Scala also supports asynchronous programming with Futures and Promises, software transactional memory, and event streams.
The most well-known open-source cluster-computing solution written in Scala is Apache Spark.
Additionally, Apache Kafka , the publish—subscribe message queue popular with Spark and other stream processing technologies, is written in Scala.
There are several ways to test code in Scala. ScalaTest supports multiple testing styles and can integrate with Java-based testing frameworks.
Scala is often compared with Groovy and Clojure , two other programming languages also using the JVM. Substantial differences between these languages are found in the type system, in the extent to which each language supports object-oriented and functional programming, and in the similarity of their syntax to the syntax of Java.
Scala is statically typed , while both Groovy and Clojure are dynamically typed. This makes the type system more complex and difficult to understand but allows almost all  type errors to be caught at compile-time and can result in significantly faster execution.
By contrast, dynamic typing requires more testing to ensure program correctness and is generally slower in order to allow greater programming flexibility and simplicity.
Regarding speed differences, current versions of Groovy and Clojure allow for optional type annotations to help programs avoid the overhead of dynamic typing in cases where types are practically static.
This overhead is further reduced when using recent versions of the JVM, which has been enhanced with an invoke dynamic instruction for methods that are defined with dynamically typed arguments.
These advances reduce the speed gap between static and dynamic typing, although a statically typed language, like Scala, is still the preferred choice when execution efficiency is very important.
Regarding programming paradigms, Scala inherits the object-oriented model of Java and extends it in various ways. Groovy, while also strongly object-oriented, is more focused in reducing verbosity.
In Clojure, object-oriented programming is deemphasised with functional programming being the main strength of the language.
Scala also has many functional programming facilities, including features found in advanced functional languages like Haskell , and tries to be agnostic between the two paradigms, letting the developer choose between the two paradigms or, more frequently, some combination thereof.
Regarding syntax similarity with Java, Scala inherits much of Java's syntax, as is the case with Groovy. Clojure on the other hand follows the Lisp syntax, which is different in both appearance and philosophy.
However, learning Scala is also considered difficult because of its many advanced features. This is not the case with Groovy, despite its also being a feature-rich language, mainly because it was designed to be mainly a scripting language.
As of [update] , all JVM-based languages Clojure, Groovy, Kotlin, Scala are significantly less popular than the original Java language, which is usually ranked first or second,   and which is also simultaneously evolving over time.