Open Source Scala Software
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Scala Software
Browse free open source Scala Software and projects below. Use the toggles on the left to filter open source Scala Software by OS, license, language, programming language, and project status.
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Scala 3
The Scala 3 compiler, also known as Dotty
Scala 3 is the latest major release of the Scala language—featuring a complete compiler rewrite (Dotty), new syntax with optional braces and given/using contextual abstractions, union/intersection types, opaque types, first-class enums, and better type inference. It unifies object-oriented and functional programming paradigms into a safer, more expressive language running on the JVM with full Java interoperability. -
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Dotty
The scala 3 compiler, also known as Dotty
The exciting new version of Scala 3 brings many improvements and new features. Scala 3 is a complete overhaul of the Scala language. At its core, many aspects of the type-system have been changed to be more principled. While this also brings exciting new features along (like union types), first and foremost, it means that the type-system gets (even) less in your way and for instance type-inference and overload resolution are much improved. One underlying core concept of Scala was (and still is to some degree) to provide users with a small set of powerful features that can be combined to great (and sometimes even unforeseen) expressivity. For example, the feature of implicits has been used to model contextual abstraction, to express type-level computation, model type-classes, perform implicit coercions, encode extension methods, and many more. Learning from these use cases, Scala 3 takes a slightly different approach and focuses on intent rather than mechanism. -
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ShadowsocksR, V2Ray Client Android
A simple client for Android
A fully featured ShadowsocksR, V2Ray and Trojan client for Android, written in Scala. If you use x64 linux like Archlinux x86_64, or your Linux has new version ncurses lib, you may need install the 32bit version ncurses and link it as follow (make sure all these *.so files in the right location under your system, otherwise you have to copy them to /usr/lib/ and /usr/lib32/ directory). -
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lichess.org
The forever free, ad-free and open source chess server
lichess.org (also known as Lila - lichess in Scala) is a free and open source chess server written in Scala 2.13 that focuses on real time gameplay and ease of use. It’s where countless chess players and chess enthusiasts can gather and watch or play from a selection of over a million games every day, analyze games, learn and improve their playing. lichess is equipped with a search engine, computer analysis, tournaments, exhibitions, a mobile app, a shared analysis board, and so much more. Thanks to its large active community, the UI is available in more than 130 different languages. lichess is one of the most popular chess websites in the world and remains totally free and ad-free. Visit https://lichess.org today to know more and see what it’s about! -
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Scala 2
Scala 2 compiler and standard library
Scala combines object-oriented and functional programming in one concise, high-level language. Scala's static types help avoid bugs in complex applications, and its JVM and JavaScript runtimes let you build high-performance systems with easy access to huge ecosystems of libraries. Scastie is Scala + sbt in your browser! You can use any version of Scala, or even alternate backends such as Dotty, Scala.js, Scala Native, and Typelevel Scala. You can use any published library. You can save and share Scala programs/builds with anybody. The Scala Library Index (or Scaladex) is a representation of a map of all published Scala libraries. With Scaladex, a developer can now query more than 175,000 releases of Scala libraries. Scaladex is officially supported by Scala Center. In Scala, functions are values, and can be defined as anonymous functions with a concise syntax. In Scala, case classes are used to represent structural data types. -
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ElasticMQ
In-memory message queue with an Amazon SQS-compatible interface
ElasticMQ is a lightweight, fully asynchronous, in-memory message queue implementation written in Scala / Akka. It provides a feature-compatible Amazon SQS REST API interface for testing, local development, or embedded usage. It can persist queues or run purely in-memory and also supports Docker deployment and a web UI. -
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Gatling
Modern Load Testing as Code
Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as well as WebSocket, Server-Sent Events, and JMS, so you can exercise modern, real-time systems end to end. Rich HTML reports visualize percentiles, response time distributions, errors, and throughput, making bottlenecks and regressions easy to spot. With injection profiles (ramp, constant, spikes) and pass/fail gates, you can automate performance thresholds in CI and promote builds with confidence. -
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sbt
sbt, the interactive build tool
Define your tasks in Scala. Run them in parallel from sbt's interactive shell. sbt is built for Scala and Java projects. It is the build tool of choice for 93.6% of the Scala developers (2019). One of the examples of a Scala-specific feature is the ability to cross-build your project against multiple Scala versions. build.sbt is a Scala-based DSL to express parallel processing task graph. Typos in build.sbt will be caught as a compilation error. With Zinc incremental compiler and file watch (~), edit-compile-test loop is fast and incremental. Adding support for new tasks and platforms (like Scala.js) is as easy as writing build.sbt. Join 100+ community-maintained plugins to share and reuse sbt tasks. Continuous compilation and testing with triggered execution. Supports mixed Scala/Java projects. Supports testing with ScalaCheck, specs, and ScalaTest. JUnit is supported by a plugin. Starts the Scala REPL with project classes and dependencies on the classpath. -
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Coursier
Pure Scala Artifact Fetching
Coursier is the Scala application and artifact manager. It can install Scala applications and setup your Scala development environment. It can also download and cache artifacts from the web. -
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Http4s
A minimal, idiomatic Scala interface for HTTP
Http4s is a minimal, idiomatic Scala interface for HTTP services. Http4s is Scala's answer to Ruby's Rack, Python's WSGI, Haskell's WAI, and Java's Servlets. http4s servers and clients share an immutable model of requests and responses. Standard headers are modeled as semantic types, and entity codecs are done by typeclass. The pure functional side of Scala is favored to promote composability and easy reasoning about your code. I/O is managed through cats-effect. http4s is built on FS2, a streaming library that provides for processing and emitting large payloads in constant space and implementing websockets. http4s cross-builds for Scala.js and Scala Native. Share code and deploy to browsers, Node.js, native executable binaries, and the JVM. -
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SpinalHDL
Scala based HDL
SpinalHDL is a hardware description (HDL) framework embedded in Scala, enabling hardware designers to build digital circuits with modern programming abstractions. Instead of writing in Verilog or VHDL directly, users describe hardware components and their interconnects using Scala code and Spinal’s domain-specific library, which then emits synthesizable hardware (e.g. as Verilog). Because SpinalHDL is embedded in Scala, it allows reuse of functional abstractions, parameterization, modular composition, and higher-level constructs to manage complexity. It supports building systems at various levels—single modules, pipelines, memories, controllers, etc.—while letting the designer control timing, pipelining, and resource sharing explicitly. The generated hardware can be synthesized for FPGAs or ASIC flows, making it practical for real designs. -
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Deequ
Deequ is a library built on top of Apache Spark
Deequ is a library built atop Apache Spark that enables defining “unit tests for data” — that is, formal constraints or checks on datasets to ensure data quality along dimensions such as completeness, uniqueness, value ranges, correlations, etc. It can scale to large datasets (billions of rows) by translating those data checks into Spark jobs. Deequ supports advanced features like a metrics repository for storing computed statistics over time, anomaly detection of data quality metrics, and the suggestion of likely constraints automatically for new datasets. It also includes a little domain-specific language called DQDL (Data Quality Definition Language) which allows declarative specification of quality rules. Users typically run Deequ before feeding data downstream (to ML pipelines, analytics, or production systems), enabling early detection and isolation of data errors. There is also a Python wrapper, PyDeequ, for users who prefer working from Python environments. -
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Monix
Asynchronous, Reactive Programming for Scala and Scala.js
Monix is a high-performance, reactive, and asynchronous programming library for Scala and Scala.js. Built as a Typelevel project, it provides advanced abstractions like Task, Observable, Iterant, and Coeval, enabling compositional, back-pressure‑aware event-driven systems that integrate cleanly with Cats Effect and Reactive Streams. -
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almond
A Scala kernel for Jupyter
Almond already supports code navigation in dependencies via meta browse, paving the way for more IDE-like features and closer integration with the Scalameta ecosystem. Ammonite is a modern and user-friendly Scala shell. Almond wraps it in a Jupyter kernel, giving you all its features and niceties, including customizable pretty-printing, magic imports, advanced dependency handling, and its API, right from Jupyter. This also makes it easy to copy some code from notebooks to Ammonite scripts, and vice versa. Almond exposes APIs to interact with Jupyter front-ends. Call them from notebooks… or from your own libraries. Several plotting libraries are already available to plot things from notebooks, such as plotly-scala or Vegas. Load the Spark version of your choice, create a Spark session, and start using it from your notebooks. -
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tapir
Declarative, type-safe web endpoints library
Declarative, type-safe web endpoints library. With tapir, you can describe HTTP API endpoints as immutable Scala values. Each endpoint can contain a number of input and output parameters. Compile-time guarantees, develop-time completions, read-time information. Separate the shape of the endpoint (the "what"), from the server logic (the "how"). Generate documentation from endpoint descriptions. Leverage the metadata to report rich metrics and tracing information. Re-use common endpoint definitions, as well as individual inputs/outputs. Library, not a framework, integrates with your stack. Is your company already using tapir? We're continually expanding the "adopters" section in the documentation; the more the merrier! It would be great to feature your company's logo, but in order to do that, we'll need to write permission to avoid any legal misunderstandings. -
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IntelliJ plugin for Haskell
IntelliJ plugin for Haskell
When I was learning Haskell, I missed the nice features of IntelliJ IDEA. My first approach was to use the default way of creating an IntelliJ plugin by defining a grammar and a lexer according to Haskell report. That didn't work out because I could not define all the recursion. Then I decided to use grammar and lexer definitions only for tokenizing and parsing Haskell code, and not for syntax checking the code. This is needed for syntax highlighting, all kinds of navigation, and so on. Further Haskell language support is provided with the help of external tools. Show error action to view formatted messages. Useful in case message consists of multiple lines (Ctrl-F10, Meta-F10 on Mac OSX); Intention actions to add language extension (depends on compiler error), add top-level type signature (depends on compiler warning). Intention action to select which module to import if the identifier is not in scope. -
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Jawn
Jawn is for parsing jay-sawn (JSON)
The term "jawn" comes from the Philadelphia area. It conveys about as much information as "thing" does. I chose the name because I had moved to Montreal so I remembered Philly fondly. Also, there isn't a better way to describe objects encoded in JSON than "things". Finally, we get a catchy slogan. Jawn was designed to parse JSON into an AST as quickly as possible. Currently, Jawn is competitive with the fastest Java JSON libraries (GSON and Jackson) and in the author's benchmarks, it often wins. It seems to be faster than any other Scala parser that exists (as of July 2014). -
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Metarank
A low code Machine Learning service that personalizes articles
Metarank is a service that can personalize any type of content: product listings, articles, recommendations and search results in 3 easy steps with a few lines of code. It’s often considered "too risky" to spend 6+ months on an in-house moonshot project to reinvent the wheel without an experienced team and no existing open-source tools. Metarank makes it easy not only for Amazon to do personalization but for everyone else. Ingest historical item listings, clicks and item metadata so Metarank can find hidden dependencies in the data using our simple JSON format.No Machine Learning experience is required, run our CLI tool with a set of features in a YAML configuration. Run Metarank API service, feed it with real-time events and receive a personalized ranking for your items that will boost conversion, click-through rate or any other business-critical metric you define. -
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Scala Steward
A bot that helps you keep your projects up-to-date
Scala Steward is an automated tool that helps to keep Scala libraries and plugins up to date by checking for dependency updates and sending pull requests. -
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ScalaCheck
Property-based testing for Scala
ScalaCheck is a library for property-based testing in Scala (and Java), inspired by Haskell’s QuickCheck. It automatically generates test inputs based on specifications, validating that properties hold across randomized scenarios, thereby enabling robust, declarative testing of edge cases and invariants. -
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Spark JobServer
REST job server for Apache Spark
Spark Job Server offers a RESTful interface for submitting, managing, and running jobs or contexts on Apache Spark. Rather than requiring every application to embed Spark or manage Spark contexts manually, this server abstracts a long-lived service where clients can upload JARs, start and stop contexts, submit jobs synchronously or asynchronously, and manage named objects (RDDs / DataFrames) across job executions. It supports multiple modes (transient jobs, persistent contexts for reuse, streaming, SQL/Hive, etc.), and can be integrated with authentication/authorization systems (e.g. via Apache Shiro). The architecture isolates Spark contexts (optionally in separate JVMs), isolates job dependencies, and persists job / jar metadata via pluggable DAOs. It supports deployment across cluster managers (YARN, Mesos, etc.) and aims to simplify Spark-as-a-service scenarios. -
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Spark NLP
State of the Art Natural Language Processing
Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task. -
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ZIO Quill
Compile-time Language Integrated Queries for Scala
ZIO Quill is a compile-time language-integrated query library for Scala, enabling the construction of type-safe and efficient database queries. It integrates with the ZIO ecosystem, providing asynchronous and composable database interactions. -
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circe
Yet another JSON library for Scala
circe is a JSON library for Scala (and Scala.js). -
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elastic4s
Elasticsearch Scala Client - Reactive, Non Blocking, Type Safe, HTTP
Elastic4s is a concise, idiomatic, reactive, type safe Scala client for Elasticsearch. The official Elasticsearch Java client can of course be used in Scala, but due to Java's syntax it is more verbose and it naturally doesn't support classes in the core Scala core library nor Scala idioms such as typeclass support. Elastic4s's DSL allows you to construct your requests programatically, with syntactic and semantic errors manifested at compile time, and uses standard Scala futures to enable you to easily integrate into an asynchronous workflow. The aim of the DSL is that requests are written in a builder-like way, while staying broadly similar to the Java API or Rest API. Each request is an immutable object, so you can create requests and safely reuse them, or further copy them for derived requests. Because each request is strongly typed your IDE or editor can use the type information to show you what operations are available for any request type.
