arcade.runner

End-to-end pipeline orchestrator (thin entrypoint over stages).

Functions

run_classify_pipeline(config_path, data_out)	Run classify (+ hardware/viz) on an existing data-stage dict.
run_pipeline(config_path, *[, cache_dir, ...])	Execute the full ARCADE pipeline.

Classes

ArcadePipeline(*[, data_stage, ...])

Injectable pipeline wiring data → classify → optimization → hardware → viz.

class arcade.runner.ArcadePipeline(*, data_stage=None, classify_stage=None, optimization_stage=None, hardware_stage=None, visualization_stage=None)

Bases: object

Injectable pipeline wiring data → classify → optimization → hardware → viz.

Pass custom stage instances to override defaults; omitted stages use the Default*Stage implementations from arcade.stages.

Wire optional custom stages into the pipeline.

Parameters:

• data_stage (BaseDataStage | None) – Data stage instance, or None for DefaultDataStage.

• classify_stage (BaseClassifyStage | None) – Classify stage instance, or None for DefaultClassifyStage.

• optimization_stage (BaseOptimizationStage | None) – Optimization stage instance, or None for DefaultOptimizationStage.

• hardware_stage (BaseHardwareStage | None) – Hardware stage instance, or None for DefaultHardwareStage.

• visualization_stage (BaseVisualizationStage | None) – Visualization stage instance, or None for DefaultVisualizationStage.

__init__(*, data_stage=None, classify_stage=None, optimization_stage=None, hardware_stage=None, visualization_stage=None)

Wire optional custom stages into the pipeline.

Parameters:

• data_stage (BaseDataStage | None) – Data stage instance, or None for DefaultDataStage.

• classify_stage (BaseClassifyStage | None) – Classify stage instance, or None for DefaultClassifyStage.

• optimization_stage (BaseOptimizationStage | None) – Optimization stage instance, or None for DefaultOptimizationStage.

• hardware_stage (BaseHardwareStage | None) – Hardware stage instance, or None for DefaultHardwareStage.

• visualization_stage (BaseVisualizationStage | None) – Visualization stage instance, or None for DefaultVisualizationStage.

Return type:

None

run(config_path, *, cache_dir=None, demod_cache_path=None)

Execute the full pipeline from config through visualization (and QEC).

Parameters:

• config_path (str | Path | dict) – Config file path, dict, or ArcadeConfig.

• cache_dir (str | Path | None) – Optional root for demod / spectral / transition caches.

• demod_cache_path (str | Path | None) – Optional explicit demod-cache file path.

Return type:

PipelineResults

Returns:

PipelineResults with data, classify, hardware, optimization, qec, and report_path.

Raises:

RuntimeError – If the data or classify stage fails fatally.

run_classify(config_path, data_out)

Run classify through visualization on an existing data-stage dict.

Parameters:

• config_path (str | Path | dict | Any) – Config file path, dict, or ArcadeConfig.

• data_out (dict[str, Any]) – Previously produced data-stage output.

Return type:

PipelineResults

Returns:

PipelineResults for the post-data stages.

arcade.runner.run_classify_pipeline(config_path, data_out)

Run classify (+ hardware/viz) on an existing data-stage dict.

Parameters:

• config_path (str | Path | dict | Any) – Config file path, dict, or ArcadeConfig.

• data_out (dict[str, Any]) – Previously produced data-stage output.

Return type:

PipelineResults

Returns:

PipelineResults for the post-data stages.

arcade.runner.run_pipeline(config_path, *, cache_dir=None, demod_cache_path=None)

Execute the full ARCADE pipeline.

Parameters:

• config_path (str | Path | dict) – Config file path or dict.

• cache_dir (str | Path | None) – Optional root for demod / spectral / transition caches.

• demod_cache_path (str | Path | None) – Optional explicit demod-cache file path.

Return type:

PipelineResults

Returns:

PipelineResults for the full run.