Open Source Scala Software for Linux - Page 5

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.

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!

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.

A web application that helps students learn Java. Students can submit their solutions to programming exercises and get immediate feedback through automated tests. The application is built with Scala and Lift.

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.

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.

Math expression parser and evaluator written in Scala. Usable from Java (Sun JRE 1.6) Provides float, integral, boolean and vector data types, some string processing support. Variables may be defined internally or im- and exported through a binding.

This project is a spin off of hipergate CRM mailing module. It has been completely rewritten in Scala and optimized for efficiently sending batches of millions of personalized emails.

Scala Native is an optimizing ahead-of-time compiler and lightweight managed runtime designed specifically for Scala. Pointers, structs, you name it. Low-level primitives let you hand-tune your application to make it work exactly as you want it to. You’re in control. Calling C code has never been easier. With the help of extern objects you can seamlessly call native code without any runtime overhead. Scala Native is compiled ahead of time via LLVM. This means that there is no sluggish warm-up phase that’s common for just-in-time compilers. Your code is immediately fast and ready for action. Scala Native requires Clang, which is part of the LLVM toolchain. The recommended LLVM version is the most recent available for your system provided that it works with Scala Native. Scala Native uses the Immix garbage collector by default. You can use the Boehm garbage collector instead. If you chose to use that alternate garbage collector both the native library and header files must be provided.

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!

Scalaffinity is a library providing a core of functionalities for any social networking web site extracting and leveraging collective intelligence. Scalaffinity is built using Scala, Spring, JPA+Hibernate(Search)+EHCache, JUnit+DBUnit, Maven...

Scalargs is a Scala library for parsing command line options as easily as possible.

Scrooge is a thrift code generator written in Scala, which currently generates code for Scala, Java, Cocoa, Android, and Lua. It’s meant to be a replacement for the Apache thrift code generator and generates conforming, binary-compatible codecs by building on top of libthrift. Since Scala is API-compatible with Java, you can use the apache thrift code generator to generate Java files and use them from within Scala, but the generated code uses Java collections and mutable “bean” classes, causing some annoying boilerplate conversions to be hand-written. This is an attempt to bypass the problem by generating Scala code directly. It also uses Scala syntax so the generated code is much more compact. There is a fairly comprehensive set of unit tests, which actually generate code, compile it, and execute it to verify expectations.

This application simplifies tracking and editing shell command history for interactive shells such as tcsh and zsh (or any shell that can be made to run a pre-execution alias or command).

This project is no longer hosted on sourceforge, please go to https://github.com/jodersky/sims instead. A library for rigid body simulation written in Scala. This project was created under the terms of a one-year project at school (Gymnase de Burier). Another program for testing and visualizing SiMS, Graphyx, is included.

Simple scala wrapper for HttpURLConnection. OAuth included. This is a fully featured http client for Scala which wraps java.net.HttpURLConnection. The library is thread safe. HttpRequest and HttpResponse are immutable. So it should be easy to wrap in an execution framework of your choice. If you're including this in some other public library. Do your users a favor and change the fully qualified name so they don't have version conflicts if they're using a different version of this library. The easiest way to do that is just to copy the source into your project.

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).

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.

SmartIMS - Smart Information Managment System

Provide a logging framework for Scala that goes beyond e.g. log4j in some interesting aspects. Besides that its API is aimed to fit well into the Scala world of programming. -- by the way: Pronounce the '4' like 'A'!

The Word Problem Solver is a program that is able to solve math word problems like they are teached in the first four classes in primary school. Currenty the program is restricted to math word problems that are presented in german language.

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.

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.

Lift is the most powerful, most secure web framework available today. There are Seven Things that distinguish Lift from other web frameworks. Lift apps are resistant to common vulnerabilities including many of the OWASP Top 10. Lift apps are fast to build, concise and easy to maintain. Lift apps are high-performance and scale in the real world to handle insane traffic levels. Lift's Comet support is unparalled and Lift's ajax support is super-easy and very secure. Because Lift applications are written in Scala, an elegant JVM language, you can still use your favorite Java libraries and deploy to your favorite Servlet Container and app server. Use the code you've already written and deploy to the container you've already configured! As of Lift 3.0, you'll need to be running Java 8 to use Lift. For those using Java 6 or Java 7, you'll need to use Lift 2.6 until you can upgrade your Java installation.

Javascript platform for tile map based single/multiplayer games with both off-line and server-based play modes. Try it out right away at http://tilescape.hg.sf.net/hgweb/tilescape/raw-file/tip/js/game.html