Open Source Scala Software Development Software
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Scala Software Development Software
View 5766 business solutionsBrowse free open source Scala Software Development Software and projects below. Use the toggles on the left to filter open source Scala Software Development Software by OS, license, language, programming language, and project status.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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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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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. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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ArnoldC
Arnold Schwarzenegger based programming language
ArnoldC is a programming language built as a joke language, where the entire syntax is based on quotes from Arnold Schwarzenegger movies. Instead of conventional keywords and operators, it uses memorable movie lines to represent programming constructs like conditionals, loops, and functions. For example, “IT’S SHOWTIME” starts the main method, “TALK TO THE HAND” represents output, and “I’LL BE BACK” denotes a return statement. While humorous in nature, the language is fully functional and can be used to write real programs, showcasing how flexible compiler and interpreter design can be. The project is a playful experiment in esoteric programming languages, intended to entertain developers while also serving as an example of how language parsing and compilation can work with unconventional syntax. It demonstrates the overlap between pop culture and software development, turning famous lines into executable logic. -
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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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GitBucket
A Git platform powered by Scala
A Git platform powered by Scala with easy installation, high extensibility & GitHub API compatibility. GitBucket is a Git web platform powered by Scala offering, easy installation, intuitive UI, high extensibility by plugins, API compatibility with GitHub. You can also deploy gitbucket.war to a servlet container which supports Servlet 3.0 (like Jetty, Tomcat, JBoss, etc). To upgrade GitBucket, replace gitbucket.war with the new version, after stopping GitBucket. All GitBucket data is stored in HOME/.gitbucket by default. So if you want to back up GitBucket's data, copy the directory to the backup location. If you want to try the development version of GitBucket, or want to contribute to the project, please see the Developer's Guide. It provides instructions on building from source and on setting up an IDE for debugging. It also contains documentation of the core concepts used within the project. -
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TextTeaser
TextTeaser is an automatic summarization algorithm
textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative. Originally inspired by research and earlier implementations, textteaser provides a lightweight solution for summarization without requiring heavy machine learning models. It is particularly useful for developers, researchers, or content platforms seeking a simple, rule-based approach to article summarization. -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Caliban
Functional GraphQL library for Scala
Caliban is a purely functional library for building GraphQL servers and clients in Scala. The design principles behind the library are the following. Minimal amount of boilerplate: no need to manually define a schema for every type in your API. Pure interface: errors and effects are returned explicitly (no exceptions thrown), all returned types are referentially transparent (no Future). Clean separation between schema definition and implementation: schema is defined and validated at compile time using Scala standard types, resolver (RootResolver) is a simple value provided at runtime. All interfaces are pure and types are referentially transparent. Schemas are type safe and derived at compile time. No need to manually define a schema for every type in your API. Let the compiler do the boring work. Out-of-the-box support for major HTTP server libraries, effect types, Json libraries and more. -
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scalajs-react
Facebook's React on Scala.JS
Scala.js React wraps Facebook React for Scala.js with a strong emphasis on type safety and functional idioms. It provides a typed virtual DOM interface, reusable components, hooks, and utilities for routing, testing, SSR, and performance profiling, all aligned with Cats, Cats Effect, and Monocle ecosystems. -
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Mozart-Oz Programming System
Runtime and development environment of Oz
The Mozart Programming System is an open source implementation of the programming language Oz 3. Oz is a multi-paradigm language that supports declarative programming, object-oriented programming, constraint programming, concurrency and distributed programming as part of a coherent whole. -
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Akka
Build concurrent, distributed, and resilient message-driven apps
Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
CoolplaySpark is a learning and practice repository designed to help users understand and work with Apache Spark. It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their understanding of Spark by not only using it as a data processing engine but also exploring how its internals function. Through code analysis and commentary, CoolplaySpark helps readers connect theoretical concepts with practical implementation details. By combining book study with this repository, learners can develop both conceptual clarity and hands-on expertise in Spark’s core components. -
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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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FiloDB
Distributed Prometheus time series database
FiloDB is an open-source distributed, real-time, in-memory, massively scalable, multi-schema time series / event / operational database with Prometheus query support and some Spark support as well. The normal configuration for real-time ingestion is deployment as stand-alone processes in a cluster, ingesting directly from Apache Kafka. The processes form a cluster using peer-to-peer Akka Cluster technology. Designed to ingest many millions of entities, sharded across multiple processes, with distributed querying built in. Support for indexing and fast querying over flexible tags for each time series/partition, just like Prometheus. Holds a huge amount of data in-memory thanks to columnar compression techniques. Designed for highly concurrent, low-latency workloads such as dashboards and alerting. Data immediately available for querying once ingested. -
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Kamon Telemetry
Distributed Tracing, Metrics and Context Propagation for applications
Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts monitoring with logs because they are there by default. Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things). -
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Mill
Your shiny new Java/Scala build tool
Your shiny new Scala build tool! Confused by SBT? Frustrated by Maven? Perplexed by Gradle? Give Mill a try. In-process tests live in the .test sub-modules of the various Mill modules. These range from tiny unit tests, to larger integration tests that instantiate a TestUtil.BaseModule in-process and a TestEvaluator to evaluate tasks on it. Note that the in-memory tests compile the BaseModule together with the test suite, and do not exercise the Mill script-file bootstrapping, transformation, and compilation process. -
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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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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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Algebird
Abstract Algebra for Scala
Algebird is Twitter’s Apache‑licensed Scala library providing abstract algebra data structures and algorithms, especially for online/streaming aggregation. It includes Monoid, Approximate, HyperLogLog, CMS, BloomFilter, Min/Max, Averaged Value types, supporting efficient distributed aggregation and approximate analytics. -
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Ammonite
Scala Scripting
Ammonite is a modern Scala REPL and scripting tool designed to give Scala users a more interactive and flexible REPL experience and to free them from heavyweight project boilerplate. It provides syntax‐highlighting, multiline editing, auto‐completion, and dynamic importing of dependencies (using a magic import syntax like import $ivy…). Instead of having to set up an sbt project for many small tasks, one can write Scala scripts (with .sc extension) and run them directly, with Ammonite handling compilation and execution transparently. In the REPL, Ammonite can survive compiler errors (by restarting the compiler internally) and preserve session state, improving resilience compared to the default Scala REPL. It also integrates filesystem utilities and command-line abstractions (via Ammonite-Ops) so that common shell tasks become more Scala-native. -
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Cats
Lightweight, modular, extensible library for functional programming
Cats is a library which provides abstractions for functional programming in the Scala programming language. The name is a playful shortening of the word category. Scala supports both object-oriented and functional programming, and this is reflected in the hybrid approach of the standard library. Cats strives to provide functional programming abstractions that are core, binary compatible, modular, approachable and efficient. A broader goal of Cats is to provide a foundation for an ecosystem of pure, typeful libraries to support functional programming in Scala applications. Cats strives to provide a solid and stable foundation for an ecosystem of FP libraries. Thus, we treat backward binary compatibility maintenance with a high priority. In semantic versioning, backward breaking change is only allowed between major versions. -
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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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Flix
The Flix Programming Language
Flix is a statically typed programming language combining functional, imperative, and logic paradigms, with first‑class Datalog constraints and a polymorphic effect system. Designed to run on the JVM, Flix enforces purity tracking at compile time, supports algebraic data types, tail‑call elimination, and allows entire Datalog programs as values.
