API

Data model

Workflow schema for Autora gui.

class autora_gui.data_model.AutoraBaseModel(*, uuid: UUID)[source]

Bases: BaseModel

Autora base model for the workflow.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

uuid: UUID

class autora_gui.data_model.CanvasLocation(*, x: int, y: int)[source]

Bases: BaseModel

A class for node’s canvas location.

Includes x and y coordinates.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

x: int

y: int

class autora_gui.data_model.Cardinality(*, minOccurs: int = 0, maxOccurs: int = 1, unique: bool = True)[source]

Bases: BaseModel

A model for cardinality in the workflow.

maxOccurs: int

minOccurs: int

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

unique: bool

class autora_gui.data_model.Component(*, uuid: UUID, canvasLocation: CanvasLocation | None)[source]

Bases: AutoraBaseModel

A component model for AutoRA GUI.

Includes canvas location.

canvasLocation: CanvasLocation | None

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class autora_gui.data_model.Datatype(value)[source]

Bases: str, Enum

Datatype model for the workflow.

ANY = 'any'

BOOLEAN = 'boolean'

CATEGORICAL = 'categorical'

DV = 'DV'

INTEGER = 'integer'

IV = 'IV'

REAL = 'real'

STRING = 'string'

Bases: VariableType

A model for dictionary variables in the workflow.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

variables: VariableTypes | list[VariableTypes]

class autora_gui.data_model.EndComponent(*, uuid: UUID, canvasLocation: CanvasLocation | None)[source]

Bases: Component

An end component model for AutoRA GUI.

Serves as the ending point of the workflow.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class autora_gui.data_model.Filter(*, source: UUID, target: UUID, maxCounter: int = 1, altTarget: UUID | None = None)[source]

Bases: Link

A filter link model for AutoRA GUI.

A specialized link with counter and alternative target.

altTarget: UUID | None

maxCounter: int

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class autora_gui.data_model.FilterComponent(*, uuid: UUID, canvasLocation: CanvasLocation | None, maxCounter: int = 1, altTarget: UUID | None = None)[source]

Bases: Component

A filter component model for AutoRA GUI.

Serves as a decision/filter point in the workflow.

altTarget: UUID | None

maxCounter: int

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class autora_gui.data_model.Link(*, source: UUID, target: UUID)[source]

Bases: BaseModel

A link (connection) model for Autora gui.

Includes output and input nodes being connected by the given link.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

source: UUID

target: UUID

class autora_gui.data_model.ListVariableType(*, name: str | None = None, description: str | None = None, variable: PrimitiveVariableType | ListVariableType | DictVariableType)[source]

Bases: VariableType

A model for list variables in the workflow.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

variable: VariableTypes

class autora_gui.data_model.ParameterSetting(*, uuid: UUID, value: str)[source]

Bases: AutoraBaseModel

A class for parameter setting.

Includes the description.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

value: str

class autora_gui.data_model.PrimitiveVariableType(*, name: str | None = None, description: str | None = None, datatype: Datatype, cardinality: Cardinality | None = None, validValues: list[str] | None = None, default: Any | None = None, sympify: bool = False)[source]

Bases: VariableType

Primitive variable type model for the workflow.

cardinality: Cardinality | None

datatype: Datatype

default: Any | None

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

sympify: bool

validValues: list[str] | None

class autora_gui.data_model.Protocol(*, uuid: UUID, protocolType: ProtocolType, name: str, description: str, githubCommit: str, github_io: str, pythonName: str, importPath: str, pipInstall: str, parameters: dict[str, list[PrimitiveVariableType | ListVariableType | DictVariableType]] | None, inputDataType: PrimitiveVariableType | ListVariableType | DictVariableType | None, outputDataType: PrimitiveVariableType | ListVariableType | DictVariableType | None, runReturnsDV: bool = False)[source]

Bases: AutoraBaseModel

A protocol model for the workflow.

Presents basic model for components and links.

description: str

githubCommit: str

github_io: str

importPath: str

inputDataType: PrimitiveVariableType | ListVariableType | DictVariableType | None

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

outputDataType: PrimitiveVariableType | ListVariableType | DictVariableType | None

parameters: dict[str, list[PrimitiveVariableType | ListVariableType | DictVariableType]] | None

pipInstall: str

protocolType: ProtocolType

pythonName: str

runReturnsDV: bool

class autora_gui.data_model.ProtocolComponent(*, uuid: UUID, canvasLocation: CanvasLocation | None, protocolUuid: UUID, parameterSetting: list[ParameterSetting] | None)[source]

Bases: Component

A protocol component model for AutoRA GUI.

Includes node parameters.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

parameterSetting: list[ParameterSetting] | None

protocolUuid: UUID

class autora_gui.data_model.ProtocolType(value)[source]

Bases: str, Enum

Protocol type model for the workflow.

EXPERIMENTALIST = 'experimentalist'

EXPERIMENT_RUNNER = 'experiment_runner'

THEORIST = 'theorist'

class autora_gui.data_model.StartComponent(*, uuid: UUID, canvasLocation: CanvasLocation | None)[source]

Bases: Component

A start component model for AutoRA GUI.

Serves as the starting point of the workflow.

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class autora_gui.data_model.VariableType(*, name: str | None = None, description: str | None = None)[source]

Bases: BaseModel

Variable type model for the workflow.

description: str | None

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str | None

class autora_gui.data_model.Workflow(*, name: str, description: str | None = None, start: StartComponent | None = None, end: EndComponent | None = None, filters: list[FilterComponent] | None = None, independentVariables: PrimitiveVariableType | ListVariableType | DictVariableType, dependentVariables: PrimitiveVariableType | ListVariableType | DictVariableType, components: list[ProtocolComponent], links: list[Link])[source]

Bases: BaseModel

A workflow model for AutoRA GUI.

Includes all possible elements like nodes and links.

components: list[ProtocolComponent]

dependentVariables: PrimitiveVariableType | ListVariableType | DictVariableType

description: str | None

end: EndComponent | None

filters: list[FilterComponent] | None

independentVariables: PrimitiveVariableType | ListVariableType | DictVariableType

links: list[Link]

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

start: StartComponent | None

autora_gui.data_model.generate_schemas(output_dir: Path | str = 'autora_gui/JSON/schemas') → None[source]

Generate JSON schemas from Pydantic models.

Parameters:: output_dir – Directory to write schema files. Defaults to autora_gui/JSON/schemas.

Utilities

autora_gui.util.find_package_location(package='autora_gui')[source]

autora_gui.util.find_repo_location(package='autora_gui')[source]

React app server

FastAPI backend for AutoRA Workflow Editor.

Run with: uvicorn server:app –reload –port 8000

class autora_gui.react_app.server.CanvasLocation(*, x: float, y: float)[source]

Bases: BaseModel

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

x: float

y: float

class autora_gui.react_app.server.ControlComponent(*, uuid: str, canvasLocation: CanvasLocation)[source]

Bases: BaseModel

canvasLocation: CanvasLocation

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

uuid: str

class autora_gui.react_app.server.FilterComponent(*, uuid: str, maxCounter: int = 1, altTarget: str | None = None, canvasLocation: CanvasLocation)[source]

Bases: BaseModel

altTarget: str | None

canvasLocation: CanvasLocation

maxCounter: int

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

uuid: str

class autora_gui.react_app.server.ParameterSetting(*, uuid: str, name: str | None = None, value: Any)[source]

Bases: BaseModel

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str | None

uuid: str

value: Any

class autora_gui.react_app.server.Workflow(*, name: str, description: str | None = None, start: ControlComponent | None = None, end: ControlComponent | None = None, filters: list[FilterComponent] = [], components: list[WorkflowComponent] = [], links: list[WorkflowLink] = [])[source]

Bases: BaseModel

components: list[WorkflowComponent]

description: str | None

end: ControlComponent | None

filters: list[FilterComponent]

links: list[WorkflowLink]

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

start: ControlComponent | None

class autora_gui.react_app.server.WorkflowComponent(*, uuid: str, protocolUuid: str, parameterSetting: list[ParameterSetting] = [], canvasLocation: CanvasLocation)[source]

Bases: BaseModel

canvasLocation: CanvasLocation

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

parameterSetting: list[ParameterSetting]

protocolUuid: str

uuid: str

class autora_gui.react_app.server.WorkflowLink(*, source: str, target: str)[source]

Bases: BaseModel

model_config = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

source: str

target: str

autora_gui.react_app.server.get_components() → dict[str, list[dict]][source]: Get all available components organized by category.

autora_gui.react_app.server.get_components_by_category(category: str) → list[dict][source]: Get components for a specific category.

autora_gui.react_app.server.get_schema(name: str) → dict[source]: Get a JSON schema by name.

autora_gui.react_app.server.lifespan(app: FastAPI)[source]

autora_gui.react_app.server.load_components() → dict[str, list[dict]][source]: Load all component JSON files organized by type.

autora_gui.react_app.server.load_schema(name: str) → dict[source]: Load a JSON schema file.

autora_gui.react_app.server.save_workflow(workflow: Workflow) → dict[source]: Save a workflow to the server (placeholder for future implementation).

autora_gui.react_app.server.validate_workflow(workflow: Workflow) → dict[source]: Validate a workflow against the schema.

React app build tooling

Build a standalone version of the React workflow editor.

This script: 1. Builds the React app with Vite 2. Combines the result into a single HTML file at the repo root

The standalone build bundles its component catalog from the JSON files in autora_gui/JSON/components at build time, so no network call is made at runtime.

autora_gui.react_app.build_standalone.create_single_html(dist_dir, output_file)[source]: Combine built assets into a single HTML file.

autora_gui.react_app.build_standalone.main()[source]

autora_gui.react_app.build_standalone.run_npm_build(react_app_dir)[source]: Run npm build to create production bundle.