thundergraph-model 1.4.0

Executable systems modeling in Python

thundergraph-model

Executable systems modeling in Python.

Model systems as System, Part, and Requirement types, compile dependency graphs, evaluate unit-aware expressions, bind external compute, and keep traceability in one strict library.

Installation

pip install thundergraph-model

Quick Start

from unitflow import kg
from tg_model import Part, System
from tg_model.execution import instantiate


class PayloadAnalysis(Part):
    @classmethod
    def define(cls, model):
        payload = model.parameter_ref(PayloadSystem, "payload_kg")
        model.attribute("payload_with_margin_kg", unit=kg, expr=payload * 1.1)
        model.constraint("payload_limit", expr=payload <= 1000 * kg)


class PayloadSystem(System):
    @classmethod
    def define(cls, model):
        model.parameter("payload_kg", unit=kg, required=True)
        model.part("analysis", PayloadAnalysis)


cm = instantiate(PayloadSystem)
result = cm.evaluate(inputs={cm.root.payload_kg: 800 * kg})

print(result.passed)
print(result.outputs[cm.root.analysis.payload_with_margin_kg.stable_id])

What It Covers

• Unit-aware parameters, attributes, and executable constraints
• Structural modeling with System, Part, and composable Requirement packages
• Requirement allocation and traceability
• Graph compilation and evaluation from Python-authored models
• External compute integration through ExternalComputeBinding
• Discrete behavior and scenario modeling

Documentation

Documentation and project information are available at thundergraph.ai/open-source/thundergraph-model.

Links

• ThunderGraph
• GitHub Repository

License

Apache 2.0