PipelineContext

class causalpy.pipeline.PipelineContext

Mutable container that accumulates results as pipeline steps execute.

Each step reads from and writes to this context, building up a complete record of the analysis.

data

The input dataset.

Type:

DataFrame

experiment

The fitted experiment object, populated by EstimateEffect.

Type:

BaseExperiment or None

experiment_config

The configuration used to create the experiment (method class + keyword arguments), so that downstream steps like SensitivityAnalysis can derive experiment factories.

Type:

dict or None

effect_summary

The effect summary from the primary experiment.

Type:

EffectSummary or None

sensitivity_results

Accumulated sensitivity / diagnostic check results.

Type:

list

report

Generated report artifact, populated by GenerateReport.

Type:

object or None

Methods

Attributes

effect_summary
experiment
experiment_config
report
data
sensitivity_results

__init__(data, experiment=None, experiment_config=None, effect_summary=None, sensitivity_results=<factory>, report=None)

Parameters:

• data (DataFrame)

• experiment (BaseExperiment | None)

• experiment_config (dict[str, Any] | None)

• effect_summary (EffectSummary | None)

• sensitivity_results (list[Any])

• report (Any)

Return type:

None

classmethod __new__(*args, **kwargs)