The Scala Programming Language for your Windows PC

Scala

Scala

  -  74.6 MB  -  Open Source
  • Latest Version

    Scala 3.7.4 LATEST

  • Review by

    Daniel Leblanc

  • Operating System

    Windows 7 / Windows 8 / Windows 10 / Windows 11

  • User Rating

    Click to vote
  • Author / Product

    Scala Team / External Link

  • Filename

    scala3-3.7.4.msi

Scala is a high-level programming language designed to bridge the gap between object-oriented and functional programming paradigms.

It runs on the Java Virtual Machine (JVM) and is often used for building scalable, high-performance applications. Initially developed by Martin Odersky, Scala is particularly popular in the fields of data science, web development, and distributed computing.

The language provides a concise, elegant syntax while offering powerful features such as immutability, pattern matching, and first-class functions.

Many large-scale applications, including those at Twitter X, LinkedIn, and Netflix, rely on Scala for its robust capabilities and seamless interoperability with Java.

Key Features

Object-Oriented & Functional – Combines the best of both programming paradigms for increased flexibility.

JVM Compatibility – Fully interoperable with Java, allowing developers to leverage existing Java libraries.

Static Typing – Detects errors at compile time, reducing runtime issues.

Scalability – Suitable for both small scripts and large-scale enterprise applications.

Concurrency Support – Offers a more concise and efficient way to handle concurrent programming.

Pattern Matching – Simplifies complex logic with powerful case classes and match expressions.

REPL (Read-Eval-Print Loop) – Interactive shell for testing and experimenting with code.

Integration with Big Data Tools – Works seamlessly with Apache Spark, Kafka, and Hadoop.

Expressive Syntax – Allows for cleaner, more readable code.

Rich Ecosystem – Supported by numerous frameworks like Play for web development and Akka for distributed applications.

User Interface

Scala does not have a graphical user interface (GUI) like traditional applications. Instead, it is used within development environments such as IntelliJ IDEA, Visual Studio Code, and Scala’s own REPL. These tools offer code completion, debugging, and syntax highlighting for a better programming experience.

For beginners, it is recommended to use IntelliJ IDEA with the plugin, as it provides a more streamlined setup with built-in support for Scala-specific development.

Installation and Setup

Download & Install Java Development Kit (JDK) – Scala runs on the JVM, so ensure JDK 8 or later is installed.

Install – Download the installer from scala-lang.org and follow the setup instructions.

Set Up an IDE – Install IntelliJ IDEA or Visual Studio Code and add the Scala plugin.

Verify Installation – Open a terminal or command prompt and type scala -version to check if Scala is installed correctly.

How to Use
  • Open a terminal or an IDE and create a new Scala project.
  • Write Scala code in a .scala file.
  • Use scalac filename.scala to compile the file.
  • Run the compiled program using scala filename.
  • Alternatively, use the interactive REPL (scala command) to execute Scala code in real-time.
FAQ

Is Scala easy to learn for beginners?
It has a steep learning curve due to its functional programming aspects, but it becomes easier with practice.

Can I use Scala with Java?
Yes, Scala is fully interoperable with Java, and you can use Java libraries within Scala code.

Is Scala still relevant in 2025?
Yes, Scala is widely used in big data, web development, and distributed systems, making it a valuable language.

Which IDE is best for Scala development?
IntelliJ IDEA with the Scala plugin is the most recommended IDE for Scala.

What are the main use cases of Scala?
Scala is mainly used for backend development, big data processing (Apache Spark), and distributed computing.

Alternatives

Python – A widely-used language for scripting and data science but lacks Scala’s static typing.

Java – Offers similar functionality but is more verbose.

Rust – Focuses on safety and performance but lacks JVM compatibility.

System Requirements
  • Operating System: Windows 10 or Windows 11
  • Processor: Intel Core i3 or higher
  • RAM: 4GB minimum (8GB recommended)
  • Disk Space: At least 500MB for installation
  • Java Version: JDK 8 or later
PROS
  • Combines object-oriented and functional programming.
  • Interoperable with Java.
  • Ideal for big data applications and distributed computing.
  • Expressive and concise syntax.
  • Strong static typing prevents runtime errors.
CONS
  • Slower compilation time compared to Java.
  • Limited adoption compared to mainstream languages like Python.
  • Requires JVM, adding an extra dependency.
  • Fewer learning resources compared to Java or Python.
Conclusion

Scala is a powerful programming language that blends object-oriented and functional paradigms, making it ideal for developers who need a scalable and efficient solution. While it has a steep learning curve, its advantages—such as JVM compatibility, concise syntax, and strong type safety—make it a compelling choice for enterprise applications, big data, and backend development.

For developers looking to work in big data, distributed computing, or large-scale enterprise systems, Scala is a solid investment. However, those seeking an easier learning experience may consider alternatives like Kotlin or Python.

Also Available: Download Scala for Mac

Why is this app published on FileHorse? (More info)
  • Scala 3.7.4 Screenshots

    The images below have been resized. Click on them to view the screenshots in full size.

    Scala 3.7.4 Screenshot 1

What's new in this version:

- Bump Scala CLI to v1.9.1 (was v1.9.0)
- Make coverage more similar to the one in Scala 2

Other changes and fixes:
Context Functions:
- Explain no expansion of ContextFunction0

Experimental: Capture Checking:
- Fix
- Fix separation checking for function results
- Simple enhancement for pattern matching with capturing types
- Don't check bounds in match type cases at CC

Experimental: Explicit Nulls:
- Add warnings for inferred flexible types in public methods and fields

Exports:
- Refine isEffectivelyFinal to avoid no-owner crash

Implicits:
- Fix LiftToAnchors for higher-kinded type applications
- Fix implicit scope liftToAnchors for parameter lower bounds

Linting:
- Invent given pattern name in for comprehension
- Unused var message mentions unread or unset
- Lint function arrow intended context function
- Always traverse Inlined.call in linter
- Ignore warnings when compiletime.testing is imported
- Lint avoids revisiting Inlined.call
- Register no elements for lint after inlining
- Use enclosing enclosingInlineds for empty call
- Exclude synthetic opaque proxy from lint

Match Types:
- Fix derivesFrom false negative in provablyDisjointClasses

Parser:
- Improve message for nested package missing braces
- Fix: Allow postfix setters under language.postfixOps
- Fix Java record varargs field accessor

Pattern Matching:
- Fix: do not transform Ident to This in PostTyper anymore
- Call inhabited for AppliedType recursively
- Fix false unreachable case warning
- Add subtype-based fallback in inferPrefixMap and recalculate constraints after application

Presentation Compiler:
- Additional completions for using clause
- Completions - do not add [] for ... derives TC@@
- Improve symbol order in completions provided by the presentation compiler
- Porting XRayModeHints
- Go to definition and hover for named args in pattern match
- Fix parameter untupling for named tuples (#23440)
- Fix possible SuspendException thrown when using macros
- Fix completions for named tuples

Reporting:
- Do not discard amended format when f-interpolator warns
- Mention named givens in double def explainer
- Compute the right span for abstract error messages
- Add quick fix to add .nn
- Add addendum to private val parameter variance error message
- Fix compiler crash with -Ymagic-offset-header

Rewrites:
- Deduplicate patches before applying them to sources

Scaladoc:
- Indicate optional parameters with = ...
- Scaladoc Support for Capture & Separation Checking
- Capture Calcuclus: don't eagerly drop caps on parameters
- Fix rendering of function-type aliases

SemanticDB:
- Add context parameters to SemanticDB synthetics
- Include synthetic apply in semanticdb

Tuples:
- Fix: make vals created in desugaring of n-ary lambdas non-synthetic

Typer:
- Prevent crash in SAM conversion with mismatched arity
- Handle assertion error in TyperState
- Correctly require a ClassTag when building a multidimensional Array
- Make isExactlyNothing and isExactlyAny work for And/OrTypes