Open Source Scala User Interface (UI) Software

Scala User Interface (UI) Software

View 124 business solutions

Browse free open source Scala User Interface (UI) Software and projects below. Use the toggles on the left to filter open source Scala User Interface (UI) Software by OS, license, language, programming language, and project status.

  • Zenflow- The AI Workflow Engine for Software Devs Icon
    Zenflow- The AI Workflow Engine for Software Devs

    Parallel agents. Multi-agent orchestration. Specs that turn into shipped code. Zenflow automates planning, coding, testing, and verification.

    Zenflow is the AI workflow engine built for real teams. Parallel agents plan, code, test, and verify in one workflow. With spec-driven development and deep context, Zenflow turns requirements into production-ready output so teams ship faster and stay in flow.
    Try free now
  • Auth0 for AI Agents now in GA Icon
    Auth0 for AI Agents now in GA

    Ready to implement AI with confidence (without sacrificing security)?

    Connect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
    Start building today
  • 1
    Metawidget
    Metawidget is a smart User Interface widget that populates itself, at runtime, with UI components to match the properties of your business objects. Supports Swing, Java Server Faces (JSF), GWT, Spring, Struts, Android, Hibernate, Groovy, JPA and more
    Downloads: 0 This Week
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  • 2
    Scalargs is a Scala library for parsing command line options as easily as possible.
    Downloads: 0 This Week
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  • 3
    Spark JobServer

    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.
    Downloads: 0 This Week
    Last Update:
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