Open Source Scala Software Development Software
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Scala Software Development Software
View 6220 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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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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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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scalafmt
Code formatter for Scala
The Scala plugin compatible with recent versions of IntelliJ IDEA has built-in support for Scalafmt. Spend more time discussing important issues in code review and less time on code style. Scalafmt formats code so that it looks consistent between people on your team. Run scalafmt from your editor, build tool or terminal. Scalafmt has integrations with IntelliJ, sbt, Maven, Gradle and Mill. Choose the scalafmt formatter and IntelliJ's Reformat Code action will then use Scalafmt when formatting files. Scalafmt is primarily designed to operate on entire text files—formatting selected ranges of code may produce undesirable results. For this reason, IntelliJ uses its own formatter for ranges by default. It is not recommended to change this, and is instead recommended to format files when saving. -
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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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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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Scala.js
Scala.js, the Scala to JavaScript compiler
Strong typing guarantees your code is free of silly mistakes; no more mixing up strings or numbers, forgetting what keys an object has, or worrying about typos in your method names. Scala.js takes care of all this tedious book-keeping for you, letting you focus on the actual, more interesting problem your application is trying to solve. Scala.js optimizes your Scala code into highly efficient JavaScript. Incremental compilation guarantees speedy (1-2s) turn-around times when your code changes. The generated JavaScript is both fast and small, starting from 45kB gzipped for a full application. Scala.js loves JavaScript libraries, including React and AngularJS. You can use any JavaScript library right from your Scala.js code, either in a statically or dynamically typed way. You won't even notice you're crossing a language border! -
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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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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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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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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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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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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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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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Sangria
Scala GraphQL implementation
Sangria is a Scala GraphQL implementation. It is an example of GraphQL server written with Play framework and Sangria. It also serves as a playground, where you can interactively execute GraphQL queries and play with some examples. If you want to use sangria with a react-relay framework, then you also may be interested in sangria-relay. Sangria is a spec-compliant GraphQL implementation, so it works out of the box with Apollo, Relay, GraphiQL and other GraphQL tools and libraries. Since GraphQL has a type system, the server defines a schema that the client can query using the introspection API. This provides the client with a set of possibilities. After the client got this information and decided which parts of the data it needs, it is able to describe its data requirements in form of a GraphQL query. An important aspect of GraphQL is that it’s completely backend agnostic. -
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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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Cats Effect
The pure asynchronous runtime for Scala
Cats-Effect is a high-quality functional programming library for Scala that provides a principled way to represent and manage side effects, particularly asynchronous and concurrent computations. It is part of the broader Typelevel ecosystem and builds on the abstractions from Cats (such as Functor, Monad, etc.). The core abstraction is the IO type (or effect types more generally), which encodes effectful computations in a pure, referentially transparent way. Cats-Effect offers capabilities like deferred execution, cancellation, resource safety (Resource), fiber concurrency (lightweight threads), and interoperation with underlying runtime platforms (JVM, Java concurrency, etc.). It enables developers to write effectful code while preserving composability, purity, and modular reasoning about side effects. -
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FS2
Compositional, streaming I/O library for Scala
FS2 (“Functional Streams for Scala”) is a purely functional, effectful abstraction for stream processing on the JVM. Built on Cats Effect, it enables compositional resource-safe streaming workflows with robust error handling, back-pressure, pull/push semantics, and support for concurrent and interruptible pipelines. -
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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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Prisma 1
Database Tools incl. ORM, migrations and admin UI
Prisma is the perfect tool for building GraphQL servers. The Prisma client is compatible with the Apollo ecosystem, has default support for GraphQL subscriptions and Relay-style pagination, provides end-to-end type safety and comes with a built-in dataloader to solve the N+1 problem. Prisma replaces traditional ORMs and simplifies database workflows. Access, Type-safe database access with the auto-generated Prisma client (in JavaScript, TypeScript, Go). Migrate, declarative data modeling and migrations (optional). Manage, visual data management with Prisma Admin. It is used to build GraphQL, REST, gRPC APIs and a lot more. Prisma currently supports MySQL, PostgreSQL, MongoDB. Prisma is a great fit for building REST& gRPC APIs where it can be used in place of traditional ORMs. It provides many benefits such as type safety, a modern API and flexible ways for reading and writing relational data. -
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Skunk
A data access library for Scala + Postgres
Skunk is a Postgres library for Scala. Skunk is powered by cats, cats-effect, scodec, and fs2. Skunk is purely functional, non-blocking, and provides a tagless-final API. Skunk gives very good error messages. Skunk embraces the Scala Code of Conduct. Skunk is pre-release software! Code and documentation are under active development! Skunk is published for Scala 2.12/2.13/3.1 and can be included in your project.Query and Command types are usually inferrable, but specifying a type ensures that the chosen encoders and decoders are consistent with the expected input and output Scala types. Postgres provides a protocol for execution of simple queries, returning all rows at once (Skunk returns them as a list). -
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Slick database
Slick (Scala Language Integrated Connection Kit) is a modern database
Slick is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred. You can write your database queries in Scala instead of SQL, thus profiting from the static checking, compile-time safety and compositionality of Scala. Slick features an extensible query compiler which can generate code for different backends. It allows you to work with relational databases almost as if you were using Scala collections, while at the same time giving you full control over when a database access happens and what data is transferred. By writing your queries in Scala you can benefit from the static type checking, compile-time safety, and compositionality of Scala, while retaining the ability to drop down to raw SQL where needed for custom or advanced database features. -
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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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Alpakka Kafka
Alpakka is a Reactive Enterprise Integration library for Java
The Alpakka project is an open source initiative to implement stream-aware and reactive integration pipelines for Java and Scala. It is built on top of Akka Streams and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure. Akka Streams is a Reactive Stream and JDK 9+ java.util.concurrent.Flow-compliant implementation and therefore fully interoperable with other implementations. As Kafka’s client protocol negotiates the version to use with the Kafka broker, you may use a Kafka client version that is different than the Kafka broker’s version. -
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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. -
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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.
