Open Source Scala Libraries
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Scala Libraries
View 72 business solutionsBrowse free open source Scala Libraries and projects below. Use the toggles on the left to filter open source Scala Libraries by OS, license, language, programming language, and project status.
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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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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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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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Refined
Refinement types for Scala
Refined is a Scala library that enhances types with compile-time constraints using predicate-style refinement types. It allows embedding validation logic into types like Refined[Int, Positive], ensuring invalid values are rejected at compile or runtime, thereby increasing safety and reducing boilerplate in domain modeling. -
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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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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. SynapseML also brings new networking capabilities to the Spark Ecosystem. With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster. -
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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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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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Ammonite
Scala Scripting
Ammonite is a Scala REPL (Read-Eval-Print Loop), scripting environment, and toolkit that enhances the default Scala REPL with smarter features: better scripting, improved imports, multi-file loading, a better interactive shell, better error messages, more convenient syntax, and utilities for file operations. It is designed to make working with Scala more pleasant in REPL / scripting use cases, not just in full projects. -
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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Binding.scala
Reactive data-binding for Scala
Binding.scala is a data-binding library for Scala, running on both JVM and Scala.js. Binding.scala can be used as the basis of UI frameworks, however latest Binding.scala 12.x does not contain any build-in UI frameworks anymore. For creating reactive HTML UI, you may want to check out html.scala, which is a UI framework based on Binding.scala, and it is also the successor of the previously built-in dom library. See also React / Binding.scala / html.scala Interoperability for using existing React components with Binding.scala. Regular HTML does not compile unless developers manually replace class and for attributes to className and htmlFor, and manually convert inline styles from CSS syntax to JSON syntax. -
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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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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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Cats Effect
The pure asynchronous runtime for Scala
Cats-Effect is a Scala library that provides a high-performance, purely functional, asynchronous runtime. It enables safe and composable effect management (i.e. side-effects, concurrency, resource safety) in functional Scala applications. It defines abstractions like IO, Resource, Concurrent, etc. It allows writing applications that manage resources safely (closing/opening, cleanup), schedule tasks, handle concurrency, define asynchronous callbacks, interoperation, and graceful shutdown. It is a core part of the Typelevel ecosystem. -
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Deequ
Deequ is a library built on top of Apache Spark
Deequ is a library built by Amazon (AWS Labs) on top of Apache Spark to enable automated data quality testing, constraint verification, and anomaly detection at scale. It lets users define assertions or constraints about data (e.g. completeness, uniqueness, min / max, correlations etc.), run metrics, verify that data meets expectations, suggest constraints, detect drift/anomaly, and integrate into data pipelines so that bad data is caught early before feeding downstream systems or ML. -
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Finch
Scala combinator library for building Finagle HTTP services
Finch is a thin layer of purely functional basic blocks atop of Finagle for building composable HTTP APIs. Its mission is to provide the developers with simple and robust HTTP primitives being as close as possible to the bare metal Finagle API. -
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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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Lagom
Reactive Microservices for the JVM
The opinionated microservices framework for moving away from the monolith. Lagom helps you decompose your legacy monolith and build, test, and deploy entire systems of Reactive microservices. Lagom is an open source framework for building systems of Reactive microservices in Java or Scala. Lagom builds on Akka and Play, proven technologies that are in production in some of the most demanding applications today. Lagom's integrated development environment allows you to focus on solving business problems instead of wiring services together. A single command builds the project, starts supporting components and your microservices, as well as the Lagom infrastructure. The build hot-reloads when it detects changes to source code. -
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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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Monocle
Optics library for Scala
Monocle is a pure functional, optics library for Scala providing immutable data access and transformation tools — including Lens, Prism, Iso, Optional, and Traversal. It enables composable, declarative modifications of deeply nested immutable structures in a concise and type-safe fashion. -
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RedRoo implements a framework for defining and executing hierarchical state machines. As a Red Kangaroo jumps from place to place, RedRoo will transition your application from state to state feeding on the events you pass to it. So get jumping!
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Regular Expression Builder for Java (reb4j) is a simple set of classes that encapsulate the regular expressions used by java.util.regex.Pattern and provide facilities for composing larger expressions from sub-expressions.
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SageMaker Spark
A Spark library for Amazon SageMaker
SageMaker Spark is an open-source Spark library for Amazon SageMaker. With SageMaker Spark you construct Spark ML Pipelines using Amazon SageMaker stages. These pipelines interleave native Spark ML stages and stages that interact with SageMaker training and model hosting. With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting your trained models, and, if you have your own ML algorithms built into SageMaker compatible Docker containers, you can use SageMaker Spark to train and infer on DataFrames with your own algorithms -- all at Spark scale. SageMaker Spark depends on hadoop-aws-2.8.1. To run Spark applications that depend on SageMaker Spark, you need to build Spark with Hadoop 2.8. However, if you are running Spark applications on EMR, you can use Spark built with Hadoop 2.7. -
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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.
