sysmlpy 0.15.0

SysML v2.0 Parser

sysmlpy

Description

sysmlpy is an open source pure Python library for constructing python-based classes consistent with the SysML v2.0 standard.

This project began as a fork of the sysml2py project by Christopher Cox. Since April 2026 Jon Fox decided to complete coverage of all SysMLv2 features over two months of weekends, and dropped the textX parser in favor of an ANTLR4 parser grammar and changed our unit library to pint. The project had diverged so much from sysml2py that a new name, sysmlpy, was selected.

v0.14.0: 100% conformance test pass rate (123/123). Storage abstraction layer with in-memory and NetworkX graph backends. Convenience functions: find_all, count, traverse, to_dict, to_graph, path_between.

v0.14.1: ISQ unit validation (300+ type-to-dimension mappings), US Customary unit support (21 custom definitions), PlantUML diagram generation with stereotype-based styling, strict import visibility enforcement, and comprehensive API documentation.

Requirements

sysmlpy requires the following Python packages:

• pyyaml
• pint
• antlr4-python3-runtime

Optional Dependencies

• networkx — graph analysis backend (install with pip install sysmlpy[graph])
• kuzu — embedded graph database with disk persistence and Cypher queries (install with pip install sysmlpy[kuzu])
• PlantUML v1.2020.0+ — diagram rendering (requires Java + PlantUML JAR or PlantUML server). The generator uses <style> blocks and skinparam stereotype selectors introduced in v1.2020.

Installation

Multiple installation methods are supported by sysmlpy, including:

Logo	Platform	Command
	PyPI	python -m pip install sysmlpy
	PyPI	python -m pip install sysmlpy[graph] (with graph analysis)
	GitHub	python -m pip install https://github.com/mycr0ft/sysmlpy/archive/refs/heads/main.zip

Documentation

Documentation can be found here.

Basic Usage

The code below will create a part called Stage 1, with a shortname of <'3.1'> referencing a specific requirement or document. It has a mass attribute of 100 kg. It has a thrust attribute of 1000 N. These attributes are created and placed as a child of the part. Next, we recall the part value for thrust and add 199 N. Finally, we can dump the output from this class.

  from sysmlpy import Attribute, Part, ureg

  a = Attribute(name='mass')
  a.set_value(100 * ureg.kilogram)
  b = Attribute(name='thrust')
  b.set_value(1000 * ureg.newton)
  c = Part(name="Stage_1", shortname="'3.1'")
  c._set_child(a)
  c._set_child(b)
  v = "Stage_1.thrust"
  c._get_child(v).set_value(c._get_child(v).get_value() + 199 * ureg.newton)
  print(c.dump())

It will output the following:

  part <'3.1'> Stage_1 {
    attribute mass= 100 [kilogram];
    attribute thrust= 1199.0 [newton];
  }

The package is able to handle Items, Parts, and Attributes.

a = Part(name='camera')
b = Item(name='lens')
d = Attribute(name='mass')
c = Part(name='sensor')
c._set_child(a)
c._set_child(b)
a._set_child(d)
print(c.dump())

will return:

part sensor {
   part camera {
      attribute mass;
   }
   item lens;
}

Actions

Actions (activities) can be defined with input and output parameters::

from sysmlpy import Action

# Action definition with typed inputs/outputs
a = Action(definition=True, name='Focus')
a.add_input('scene', 'Scene')
a.add_output('image', 'Image')
print(a.dump())
# → action def Focus { in scene : Scene; out image : Image; }

# Action usage with references
b = Action(name='TakePicture')
b.add_input('scene')
b.add_output('picture')
print(b.dump())
# → action TakePicture { in scene; out picture; }

References

References can reference other elements::

from sysmlpy import Reference, Item

# Simple reference
r = Reference(name='driver')
print(r.dump())
# → ref driver;

# Reference with type
person = Item(name='Person')
r2 = Reference(name='driver')
r2.set_type(person)
print(r2.dump())
# → ref driver : Person;

# Reference redefinition
r3 = Reference(name='payload', redefines=True)
r3.set_type(person)
print(r3.dump())
# → ref :>> payload : Person;

Grammar Round-Trip

loads() parses SysML v2 text and classtree() converts the result back to text. This round-trip is the basis for the grammar test suite.

from sysmlpy import loads
from sysmlpy.formatting import classtree

text = """package 'Action Example' {
    action def Focus { in scene : Scene; out image : Image; }
    action def Shoot { in image: Image; out picture : Picture; }

    action def TakePicture {
        in item scene : Scene;
        out item picture : Picture;

        bind focus.scene = scene;

        action focus : Focus { in scene; out image; }

        flow focus.image to shoot.image;

        first focus then shoot;

        action shoot : Shoot { in image; out picture; }

        bind shoot.picture = picture;
    }
}"""

model = loads(text)
tree = classtree(model)
print(tree.dump())

61% of the 56 grammar round-trip tests currently pass (34/56), covering packages, parts, items, ports, interfaces, binding connectors, flow connections, all action forms (definition, shorthand, succession, decomposition), expressions, calculations, and constraints.

PlantUML Visualizations

Generate SysML v2 structure diagrams from parsed models using the built-in PlantUML generator. Definitions render with sharp corners and usage elements with rounded corners. Relationships are differentiated by arrow style, thickness, and color — following the official SysML v2 Pilot Implementation approach.

from sysmlpy import loads
from sysmlpy.plantuml import PlantUMLGenerator

text = """package Vehicle {
    part def Wheel {
        attribute radius : LengthValue;
        attribute pressure : PressureValue;
    }

    part def BrakeSystem {
        attribute padThickness : LengthValue;
    }

    part def VehicleAssembly {
        part frontLeft : Wheel;
        part frontRight : Wheel;
        part brakes : BrakeSystem;
    }

    part myVehicle : VehicleAssembly;
}"""

model = loads(text)
gen = PlantUMLGenerator(model, title="Vehicle Structure")
print(gen.generate())

Produces PlantUML source that renders as:

@startuml
skinparam RoundCorner 0
skinparam rectangle<<(D,#8B4513) part def>> {
    RoundCorner 0
    BackgroundColor #FFF8F0
    BorderColor #8B4513
}
skinparam rectangle<<(P,#32CD32) part>> {
    RoundCorner 15
    BackgroundColor #F0FFF0
    BorderColor #32CD32
}

title Vehicle Structure

rectangle "Wheel" as Wheel <<(D,#8B4513) part def>>
rectangle "BrakeSystem" as BrakeSystem <<(D,#8B4513) part def>>
rectangle "VehicleAssembly" as VehicleAssembly <<(D,#8B4513) part def>>
rectangle "myVehicle" as myVehicle <<(P,#32CD32) part>>

VehicleAssembly *-- frontLeft : owns
VehicleAssembly *-- frontRight : owns
VehicleAssembly *-- brakes : owns
myVehicle --:|> VehicleAssembly : types

legend right
  <b>Legend</b>
  |= Element |= Notation |
  | <<(D,#8B4513) part def>> | Definition (type) |
  | <<(P,#32CD32) part>> | Usage (instance) |
  | --:|> | Feature typing |
  | *-- | Composite containment |
endlegend
@enduml

Filtering and Focus

The generator supports filtering to highlight specific elements:

# Show only elements related to 'myVehicle'
gen = PlantUMLGenerator(model, focus="myVehicle")

# Show a custom set of elements
gen = PlantUMLGenerator(model, elements=["Wheel", "BrakeSystem"])

# Limit nesting depth
gen = PlantUMLGenerator(model, max_depth=2)

See docs/plantuml-examples/ for 9 rendered examples covering usage vs definition, relationships, vehicle structure, requirements, interconnections, state machines, and activity diagrams.

Conformance

100% of 123 OMG XPect conformance tests pass (123/123).

License

sysmlpy is released under the MIT license, hence allowing commercial use of the library.