scala variable multiple assignment

15 Declare multiple variables

It is possible to declare and assign multiple variables to the same value.

The types of the variables in this example are inferred.

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• Scala Tutorials

How to Declare Scala Variables – Scope & Examples

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What are Scala variables, and how do we declare them? What is type inference? How do we perform multiple assignments? What is the variable scope? These are the questions we’ll be answering today.

So, let’s start Scala Variables Tutorial.

Introduction to Variables in Scala

A variable is a reserved memory location to store values. The compiler allocates memory and decides what goes in based on a variable’s data type. We can assign different types like integers, characters, or decimals to variables. Let’s begin.

Declaring Scala Variables

We can declare a Scala variable as a constant or as a variable:

a. Constant

To declare a value that we cannot mutate/change, we use the keyword ‘val’. This is immutable.

b. Variable

A variable is mutable. We can change its value as many times as we like. Declare it using the keyword ‘var’.

Scala Variables Type Inference

When we assign an initial value to a variable, the compiler infers its type based on the types of the subexpressions and the literals. This means that we don’t always have to declare the type of a variable.

Scala Variable Data Types

We can specify a variable’s type after a colon after its name. Take an example:

Multiple Assignments

How do we fit multiple assignment statements into one statement? We assign a Tuple to a val variable.

Scala Variable Scope

We have three kinds of scopes for Scala variables. Let’s see them one by one.

If an object owns a variable, the variable is a field in it. We can access fields from inside every method in the object. Well, we can also access them outside the object if we declared them with the right access modifiers. A field may be mutable or immutable, and we can define them using ‘var’ or ‘val’.

b. Method Parameters

A method parameter is a variable that we can use to pass a value inside a method when we call it. We can only access it inside the method, but if we have a reference to that object from outside the method, we can access the objects from outside. A method parameter is always immutable, and we define it using the ‘val’ keyword.

c. Local Variables

A local variable is one we declare inside a method. While we can only access it from inside a method, if we return the objects, that we create, from the method, they may escape it. A local variable may be mutable or immutable, and we may define it using the keywords ‘var’ or ‘val’.

So, this was all about Scala Variables. Hope you like our explanation.

Hence, we discussed about how to declare Scala variables, type inference, data type, and scope. If you have any query regarding Scala Variables, please comment. See you again with another topic to learn with Scala. Have a good day.

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Tags: Creating Variables in Scala Scala globle variable Scala variable scope Scala Variables

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Please add examples in point 7

while declaring variables of method parameters in scala why we don’t use var or val

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Variables are nothing but reserved memory locations to store values. This means that when you create a variable, you reserve some space in memory.

Based on the data type of a variable, the compiler allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you can store integers, decimals, or characters in these variables.

Variable Declaration

Scala has a different syntax for declaring variables. They can be defined as value, i.e., constant or a variable. Here, myVar is declared using the keyword var. It is a variable that can change value and this is called mutable variable . Following is the syntax to define a variable using var keyword −

Here, myVal is declared using the keyword val. This means that it is a variable that cannot be changed and this is called immutable variable . Following is the syntax to define a variable using val keyword −

Variable Data Types

The type of a variable is specified after the variable name and before equals sign. You can define any type of Scala variable by mentioning its data type as follows −

If you do not assign any initial value to a variable, then it is valid as follows −

Variable Type Inference

When you assign an initial value to a variable, the Scala compiler can figure out the type of the variable based on the value assigned to it. This is called variable type inference. Therefore, you could write these variable declarations like this −

Here, by default, myVar will be Int type and myVal will become String type variable.

Multiple assignments

Scala supports multiple assignments. If a code block or method returns a Tuple ( Tuple − Holds collection of Objects of different types), the Tuple can be assigned to a val variable. [ Note − We will study Tuples in subsequent chapters.]

And the type inference gets it right −

Example Program

The following is an example program that explains the process of variable declaration in Scala. This program declares four variables — two variables are defined with type declaration and remaining two are without type declaration.

Save the above program in Demo.scala . The following commands are used to compile and execute this program.

Variable Scope

Variables in Scala can have three different scopes depending on the place where they are being used. They can exist as fields, as method parameters and as local variables. Below are the details about each type of scope.

Fields are variables that belong to an object. The fields are accessible from inside every method in the object. Fields can also be accessible outside the object depending on what access modifiers the field is declared with. Object fields can be both mutable and immutable types and can be defined using either var or val .

Method Parameters

Method parameters are variables, which are used to pass the value inside a method, when the method is called. Method parameters are only accessible from inside the method but the objects passed in may be accessible from the outside, if you have a reference to the object from outside the method. Method parameters are always immutable which are defined by val keyword.

Local Variables

Local variables are variables declared inside a method. Local variables are only accessible from inside the method, but the objects you create may escape the method if you return them from the method. Local variables can be both mutable and immutable types and can be defined using either var or val .

• Two Types of Variables

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In Java you declare new variables like this:

Each variable declaration is preceded by its type.

By contrast, Scala has two types of variables:

• val creates an immutable variable (like final in Java)
• var creates a mutable variable

This is what variable declaration looks like in Scala:

Those examples show that the Scala compiler is usually smart enough to infer the variable’s data type from the code on the right side of the = sign. We say that the variable’s type is inferred by the compiler. You can also explicitly declare the variable type if you prefer:

In most cases the compiler doesn’t need to see those explicit types, but you can add them if you think it makes your code easier to read.

As a practical matter it can help to explicitly show the type when you’re working with methods in third-party libraries, especially if you don’t use the library often, or if their method names don’t make the type clear.

The difference between val and var

The difference between val and var is that val makes a variable immutable — like final in Java — and var makes a variable mutable . Because val fields can’t vary, some people refer to them as values rather than variables.

The REPL shows what happens when you try to reassign a val field:

That fails with a “reassignment to val” error, as expected. Conversely, you can reassign a var :

In Scala the general rule is that you should always use a val field unless there’s a good reason not to. This simple rule (a) makes your code more like algebra and (b) helps get you started down the path to functional programming, where all fields are immutable.

“Hello, world” with a val field

Here’s what a “Hello, world” app looks like with a val field:

• Save that code in a file named Hello3.scala
• Compile it with scalac Hello3.scala
• Run it with scala Hello3

A note about val fields in the REPL

The REPL isn’t 100% the same as working with source code in an IDE, so there are a few things you can do in the REPL that you can’t do when working on real-world code in a project. One example of this is that you can redefine a val field in the REPL, like this:

val fields can’t be redefined like that in the real world, but they can be redefined in the REPL playground.

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• Introduction
• Prelude꞉ A Taste of Scala
• Preliminaries
• Scala Features
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• Hello, World - Version 2
• The Scala REPL
• The Type is Optional
• A Few Built-In Types
• Two Notes About Strings
• Command-Line I/O
• Control Structures
• The if/then/else Construct
• for Expressions
• match Expressions
• try/catch/finally Expressions
• Scala Classes
• Auxiliary Class Constructors
• Supplying Default Values for Constructor Parameters
• A First Look at Scala Methods
• Enumerations (and a Complete Pizza Class)
• Scala Traits and Abstract Classes
• Using Scala Traits as Interfaces
• Using Scala Traits Like Abstract Classes
• Abstract Classes
• Scala Collections
• The ArrayBuffer Class
• The List Class
• The Vector Class
• The Map Class
• The Set Class
• Anonymous Functions
• Common Sequence Methods
• Common Map Methods
• A Few Miscellaneous Items
• An OOP Example
• sbt and ScalaTest
• The most used scala build tool (sbt)
• Using ScalaTest with sbt
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Def, Var & Val in Scala

Last updated: March 18, 2024

• Scala Basics

1. Overview

In this tutorial, we’ll explore the similarities and differences between methods, variables, values, and lazy values.

For more information on Scala’s core features, refer to our Intro and Guide to lazy val.

Methods are lazily evaluated, which means their evaluation is delayed until we call them . We can check the evaluation strategy by writing a method that prints something to the console:

Based on the console output, we verify that methods evaluate every time we call them:

Methods are also immutable, therefore we can’t change their values after we create them. When we try to do it, the compiler will fail with a “secretNumber_= is not a member of object” message:

3. Variables

Variables, unlike methods, evaluate eagerly . Their evaluation happens only once during the declaration:

We can see that the evaluation of variables occurs only once, during declaration:

Unlike methods, variables are mutable as we can change their value after we create them:

Values, similarly to variables, are eagerly evaluated as their evaluation occurs during declaration:

Console output:

On the other hand, values, unlike variables are immutable. When we try to assign a new value, the compiler fails with a “reassignment to val” message:

5. Lazy Values

Lazy values have an exciting property. Unlike values, they are lazily evaluated, but in contrast to methods, the evaluation happens only once:

We see that the evaluation   occurs during the first usage of lazyValue :

On the other hand, lazy values are immutable. Similarly to values, the compiler will fail with a “reassignment to val” message when we try to assign a new value to them:

6. Conclusion

In this short tutorial, we learned about the similarities and differences between methods, variables, values, and lazy values. We focused on their evaluation strategy and mutability.

As always, the source code with all the examples used in this tutorial is available over on GitHub .

Pre-SIP: multiple assignments

Introduction.

This proposal discusses the syntax and semantics of a construct to assign multiple variables with a single expression. This feature would simplify the implementation of operations expressed in terms of relationships between multiple variables, such as std::swap in C++.

It happens that one has to assign multiple variables “at once” in an algorithm. For example, let’s consider the Fibonacci sequence:

The same iterator could be rewritten more concisely if we could assign multiple variables at once. For example, we can write the following in Swift:

Though the differences may seem frivolous at first glance, they are in fact important. If we look at a formal definition of the Fibonacci sequence (e.g., on Wikipedia ), we might see something like:

The Fibonacci sequence is given by F(n) = F(n-1) + F(n+1) where F(0) = 0 and F(1) = 1 .

Although this declarative description says nothing about an evaluation order, it becomes a concern in our Scala implementation as we must encode the relationship into multiple operational steps. This decomposition offers opportunities to get things wrong:

In contrast, our Swift implementation can remain closer to the formal definition and is therefore more legible and less error-prone.

Multiple assignments show up in many general-purpose algorithms (e.g., insertion sort, partition, min-max element, …). But perhaps the most fundamental one is swap , which consists of exchanging two values.

We often swap values that are stored in some collection. In this particular case, all is well in Scala because we can ask the collection to swap elements at given positions:

Sadly, one can’t implement a generic swap method that wouldn’t rely on the ability to index a container. The only way to express this operation in Scala is to “inline” the pattern implemented by swapAt every time we need to swap two values.

Having to rewrite this boilerplate is unfortunate. Here is an example in a realistic algorithm:

Note: implementation shamelessly copied from swift-algorithms .

The swap occurs once in the middle of the method with the sequence of expressions val t = l; l = h; h = l and a second time in the loop. To borrow from the words of Edgar Dijskstra [1, Chapter 11]:

[that] is combersome and ugly compared with the [multiple] assignment.

We can find countless other examples of swap in languages that enjoy this operation, such as Swift, C++, and Rust. There are even programming idioms based on its use (e.g., exception safety in C++ ).

Proposed solution

The proposed solution is to add a language construct to assign multiple variables in a single expression:

Using this construct, the above Fibonacci iterator can be rewritten as:

Multiple assignments also alleviate the need for a swap method on collections, as the same idiomatic pattern can be reused to exchange elements at given indices:

Detailed design

A multiple assignment is an expression of the form AssignTarget ‘=’ Expr where:

An assignment target describes a tree that can only be matched by a compatible composition of tuples. For example, the following program is legal.

A mismatch between the structure of a multiple assignment’s target and the result of its RHS is a type error. It cannot be detected during parsing because at this stage the compiler would not be able to determine the shape of an arbitrary expression’s result. For example, all multiple assignments in the following program are ill-typed:

Note that (x) = Tuple1(false) is not equivalent to x = Tuple1(false) . The former is a multiple assignment while the latter is a regular assignment, as described by the current grammar (see Expr1 ). Though this distinction is subtle, multiple assignments involving unary tuples should be rare.

The operational semantics of multiple assignments (aka concurrent assignments) have been studied extensively in scienific literature (e.g., [1, 2]). A first intuition is that the most desirable semantics can be achieved by fully evaluating the RHS of the assignment before assigning any expression in the LHS [1]. However, additional considerations must be given w.r.t. the independence of the variables on the LHS to guarantee deterministic results. For example, consider the following expression:

While one may conclude that such an expression should be an error [1], it is in general difficult to guarantee value independence in a language with pervasive reference semantics. Further, it is desirable to write expressions of the form (a(0), a(2)) = (a(2), a(0)) , as shown in the previous section.

To address these issues, we define the following algorithm:

• Compute the value of the RHS, which forms a tree of values
• Traverse the LHS and RHS structures pairwise in inorder, performing assignment for each pair of leaves.

For instance, the evaluation of the expression ((x, a(1)), x) = (f, false) is as follows:

• evaluate (f, 9000) ; the result is a tree ((true, 42), false)
• assign x to true
• assign a(1) to 42
• assign x to false

After the assignment, x == false and a(1) == 42 .

The compiler is allowed to modify this order for optimization purposes as long as it can guarantee that such a change is not observable. For example, the assignments of x and y in (x, y) = (1, 2) can be reordered or even performed in parallel.

Impact on existing code

One understandable concern of the proposed syntax is that the semantics of multiple assignments resembles that of pattern matching, yet it has different semantics. For example:

If a is instance of a type with a companion extractor object, the two lines above have completely different semantics. The first declares two local bindings x and b , applying pattern matching to determine their value from the tuple (true, "!") . The second is assigning a(x) and b to the values true and "!" , respectively.

Though possibly surprising, the difference in behavior is easy to explain. The first line applies pattern matching because it starts with val . The second doesn’t because it involves no pattern matching introducer. Further, note that a similar situation can already be reproduced in current Scala:

• Edsger W. Dijkstra: A Discipline of Programming. Prentice-Hall 1976, ISBN 013215871X
• Ralph-Johan Back, Joakim von Wright: Refinement Calculus - A Systematic Introduction. Graduate Texts in Computer Science, Springer 1998, ISBN 978-0-387-98417-9

On the principle, I’m not against this change, it would be a neat niche feature (We probably disagree on whether it would be niche, but I believe the semantics are more important first)

I would like to clarify the exact semantics, in the case of (a(0), p.x) = (b, c) , Do we agree that the following happens:

• Evaluate b , let’s call the result v_b
• Evaluate c , let’s call the result v_c
• Evaluate (v_b, v_c) , let’s call the result v_pair
• Evaluate a.update(0, v_pair._1)
• Evaluate p.x_=(v_pair._2) in the case where it is the most applicable (which is not the common case)

(I skipped the evaluate a and evaluate p )

Yes, that is the evaluation order I am proposing.

Then I see no technical issues right now.

As I hinted at before I don’t really see a semantic or syntactic issue with it either, it feels like a very natural extension of the language !

So the only negative I see with it is the work necessary to implement and maintain it, and whether that work is worth it for this feature.

I see the usefulness as low (in part because I tend to gravitate to immutable structures), so the question becomes how hard is it to implement ?

If easy, I think this is worth it If hard, maybe not so much

But I’m open to being convinced otherwise !

Is the intent to bless the update method, or specialize this behavior to the standard library?

Just looking at potential interactions with other features

Thinking more on it, I think it could be more regular, when we do:

We’re really just doing:

I would therefore expect the following to work as well:

Which would desugar in a similar way:

I am in favour of this new language feature. It always stunned me that if you have some lengthy calculation that produces two values in a tuple:

you can state:

but in case a and b are variables you must do

The new solution is much cleaner, and imho, what you naively expect.

There are very clear use cases for this feature in the context of immutable data structures. In fact, I discovered the language limitation as I was trying to implement value semantics in Scala.

There is a straightforward correspondence between in-place mutation and so-called “functional updates”. Consider the following:

Immutability enthusiasts will probably be repulsed by the var s in Vec2 and offer this code instead:

Note: The real enthusiasts will also complain about the var in the main function and claim that we should declare another variable instead.

What’s interesting to observe, though, is that if one can guarantee that v is not aliased anywhere, then there the two programs are notionally equivalent. So if can you maintain value independence, that is if you can guarantee that “mutating” something has no observable effect on any other value, then mutation becomes completely harmless. To convince yourself that it’s true, you merely have to rewrite your in-place mutation into a functional update.

So how can we generalize the relationship between scaleInPlace and scale ? Well, we simply have to say that every argument that is “mutated” in an in-place mutating function (A1, ..., An) -> R is returned along with R . And then you wish you had multiple assignments to remove the noisy boilerplate involve in extracting results and assign them back to the original variable.

I’m happy to expand on this topic but it would be a little tangential to this Pre-SIP. So if people are interested I’ll open a different thread. Alternatively one can have a look at this paper: Implementation Strategies for Mutable Value Semantics .

I see what you mean, but what I’d really like is to write

And the compiler rewrites it as:

(Or even just val v = Vec2(2, 4) )

I.E. I really don’t want to deal with mutability as an end-user, as a library designer, if I have to use some to make things fast, I don’t mind some boilerplate

It works already, if this is what you want to do:

Yes, in this form it works:

but not in the form i used above:

I think this was requested in the ancient past. Possibly a T rex requested it.

In honor of the current thread, I submitted a fix for the message when one of co-defined vars is unused or not updated :

Instead of saying “make it a val, what’s the problem?”, it will suggest refactoring, i.e., re-engineering the definition. Probably you will say, Did you add a quick fix? and the answer is no, I didn’t think of doing that.

Edit: periodic reminder that tickets from 2013 are now ten years old. That is not their default. As my daughter would remind me, they did not ask to be born.

One thing that will be particularly tricky to get right is evaluation order. The initial post already gives a pretty good definition, but it omits a discussion of the evaluation order of the left -hand-side. When the components of the left-hand-side are all local variables, that is not an issue, but when they are more complicated, it becomes difficult.

The current semantics of assignment in the presence of a complicate left-hand-side are as follows.

the prefix must be evaluated first, then rhs , then the method field_= is called.

the obj is evaluated first, then the arg1, ..., argN, rhs , in order, then update is called.

If we put these two kinds of things into multi-assignment statements, it is not clear what the exact semantics will have to be:

what do we evaluate when?

To keep the overall left-to-right evaluation, it seems we should do

• arg1, ..., argN
• call field_=
• call update_=

There is also the NullPointerException s to think about. On the JVM it will naturally happen at the time of field_= / update_= . In JS however the NPE UB triggers earlier. In a method call x.m(args) it triggers right after evaluating x . We’ll probably want it to happen right after evaluating prefix and then after obj , to be consistent.

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Assigning Multiple Variables in One Line in Python

In this video, we will explore how to assign multiple variables in one line in Python. This technique allows for concise and readable code, especially when you need to initialize multiple variables simultaneously. This tutorial is perfect for students, professionals, or anyone interested in enhancing their Python programming skills.

Why Assign Multiple Variables in One Line?

Assigning multiple variables in one line helps to:

• Write more concise and readable code.
• Initialize multiple variables simultaneously.
• Simplify code maintenance and debugging.

Key Concepts

1. Multiple Assignment:

• The ability to assign values to multiple variables in a single line of code.

2. Tuple Unpacking:

• A technique that allows you to assign values from a tuple to multiple variables in one line.

How to Assign Multiple Variables in One Line

1. Basic Multiple Assignment:

• Assign values to multiple variables separated by commas.
• Use tuples to assign multiple variables in a single line.

3. List Unpacking:

• Similar to tuple unpacking, but using lists.

Practical Examples

Example 1: Basic Multiple Assignment

• Assign values to multiple variables in one line.
• Example: a, b, c = 1, 2, 3

Example 2: Tuple Unpacking

• Use tuple unpacking to assign values.
• Example: x, y = (4, 5)

Example 3: List Unpacking

• Use list unpacking to assign values.
• Example: m, n, o = [6, 7, 8]

Practical Applications

Data Initialization:

• Initialize multiple variables with values in one line for cleaner and more concise code.

Function Returns:

• Assign multiple return values from a function call to separate variables in one line.

Swapping Variables:

• Swap values of two variables in one line using tuple unpacking.
• Example: a, b = b, a

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Multiple assignment from a vector to individual variables

In my test suite I am frequently writing code such as

foo obviously returns a (short) Vector but I'd like to have names for each of the values. It's not always four items long, but since it's my test suite the correct number is known and I'm perfectly fine with an exception being thrown if there is a length mismatch.

The above code works -- except that I get a compiler error:

Is there a way to get rid of the compiler warning? I've tried @nowarn and @nocheck in various positions with no luck.

Alternatively, is there a succinct way to write this so it doesn't cause a warning in the first place? The solution at Convert Vector to Tuple scala looks promising except that reflection isn't available for ScalaJS.

Is there an approach using a builder or something?

Thanks to Dmytro Mitin for reminding me to check my compiler options. Yes, I had completely forgotten about that and had -Xlint:valpattern enabled. Turning that off removes the warning.

That solves my immediate problem. But as a challenge, is there a way to implement toTuple without using reflection?

• pattern-matching
• compiler-warnings
• non-exhaustive-patterns

• 2 scastie.scala-lang.org/DmytroMitin/Jb0A5lWYQHKKoESw0v8T0Q As you can see by default there is no warning. Show your scalacOptions switched on. –  Dmytro Mitin Commented Mar 28, 2023 at 20:06
• It looks like it should be returning a case class instead of a vector –  michaJlS Commented Mar 28, 2023 at 20:23
• @DmytroMitin, thanks for the reminder. You're spot-on, as you can see in my update. Not sure how to credit you other than with this comment. Thanks! –  bwbecker Commented Mar 28, 2023 at 22:01
• @michaJlS, I'm not returning a case class because the length can vary. In the main body of my code I process it as a vector. But in testing I want to look at the attributes of individual elements. Having them assigned to variables makes that easier. –  bwbecker Commented Mar 28, 2023 at 22:03

You can switch off -Xlint:valpattern .

But if you want to keep -Xlint:valpattern and switch off the warning match may not be exhaustive in this specific place you can use @unchecked

If a vector returned by foo can be longer than 4 elements you can additionally use vararg pattern

You can also transform a vector into a tuple with Shapeless . I can't see direct Vector => Tuple , so I'm using Vector => HList => Tuple

On contrary to runtime reflection, this mostly works at compile time (we're specifying 4 statically, otherwise .get will throw java.util.NoSuchElementException: None.get at runtime), so this should work in ScalaJS too

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