Semantiva

Overview

Semantiva is an open-source, Python-based framework that unifies Domain-Driven Design, Type-Oriented Development, and semantic transparency to streamline data operations. It offers a structured way to define and process domain-specific data types and algorithms, ensuring clarity, consistency, and adaptability even in complex scenarios.

Semantiva enforces type-safe relationships between data and algorithms and uses a dual-channel pipeline model where payload and context flow together. This enables dynamic parameter injection, traceable execution, and high reusability across workflows.

Install

pip install semantiva

Getting Started

Quickstart — Hello pipeline (YAML only)

Create hello.yaml:

extensions: ["semantiva-examples"]

pipeline:
  nodes:
    - processor: FloatValueDataSource
      parameters:
        value: 1.0

    - processor: FloatAddOperation
      parameters:
        addend: 2.0

    - processor: FloatMultiplyOperation
      parameters:
        factor: 10.0

    - processor: FloatCollectValueProbe
      context_key: "result"
    - processor: template:"result_{result}.txt":path
    - processor: FloatTxtFileSaver

Run it:

semantiva run hello.yaml

This writes the computed result to the output file defined dynamically by the context.

For the complete guide, visit https://api.semantiva.org

Why Semantiva?

Semantiva is a semantic framework for reproducible, contract-validated workflows:

• Pipelines compile into deterministic graphs with stable semantic/configuration IDs.
• Components are validated through a contract catalog.
• Payload and context travel together to enable dynamic behavior and rich introspection.
• Supports parametric sweeps, context-driven adaptation, and pluggable execution backends.

Key Principles

1. Domain-Driven Design (DDD)
2. Type-Oriented Development
3. Semantic Transparency & AI-Readiness

Features

• Semantic components with machine-readable metadata
• Deterministic graph identity (semantic + configuration)
• Contract-validated processors
• Typed payloads and structured context
• Parametric sweeps defined in YAML
• Modular, extensible execution layer
• Optional tracing with deterministic IDs
• HPC- and AI-ready architecture

Benefits

• Clarity & consistency across pipelines
• Adaptive workflows that evolve with domain needs
• Scalable to HPC environments
• AI-driven collaboration possible due to explicit semantics
• Interdisciplinary communication through shared data/operation types
• Dynamic parameter injection via the context stream

Core Components

1. Data Operations — type-safe payload transformations
2. Context Processors — metadata and runtime parameter management
3. Pipelines — orchestrated execution of operations
4. Data Types & Processor Types — explicit semantic structures
5. Execution Tools — CLI, tracing, inspection utilities

Pipeline Configuration & Node Factories

Pipelines are defined declaratively in YAML. Node factories:

• Instantiate processors
• Wire payload + context flows
• Resolve parameters
• Compute stable identities

This separation of configuration and implementation supports reproducibility and controlled evolution of workflows.

License

Semantiva is released under the Apache License 2.0.

Acknowledgments

Semantiva draws inspiration from the transparency and traceability requirements of large-scale scientific computing systems, notably the ALICE O² project at CERN. Lessons from managing high-throughput, HPC-oriented workflows in that environment helped shape Semantiva’s focus on typed workflows, semantic clarity, provenance, and robust execution architecture.