Python API

Documentation of PETsARD’s Python API.

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Important Note: This package expects users to control execution using Executor with YAML. Users are not expected to directly use internal modules. This documentation is for internal development team reference only. Any changes to these module functions will not be considered BREAKING CHANGES and backward compatibility is not guaranteed.

Design Principles

Adapter Pattern

Uses the adapter design pattern to unify module interfaces through the Adapter layer, allowing Executor to execute all components consistently:

create() - Create instance
fit_sample() / eval() / report() - Execute methods (train and generate / execute evaluation / output report)

Each module is wrapped by an Adapter to ensure standardized external interfaces.

Immutable Objects

All configuration classes are frozen dataclasses to ensure data safety.

Type Hints

Complete type annotations for better development experience.

Configuration and Execution

Module	Function
Executor	Main interface for experiment pipeline, coordinates entire data synthesis and evaluation workflow

Data Management

Module	Function
Metadater	Dataset structure and metadata management, handles data type definitions and validation

Pipeline Components

Module	Function
Benchmarker	Benchmark dataset management, automatic downloading and processing of benchmark data
Loader	Data loading and processing, supports multiple file formats
Splitter	Experiment data splitting, supports train/test set splitting
Processor	Data preprocessing and postprocessing, includes encoding and normalization
Synthesizer	Synthetic data generation, supports multiple synthesis algorithms
Constrainer	Data constraint processor for synthetic data, ensures data meets business rules
Evaluator	Privacy, fidelity and utility evaluation, provides multi-dimensional quality assessment
Describer	Descriptive data summary, provides statistical analysis
Reporter	Result export and reporting, supports multiple output formats

System Components

Module	Function
Adapter	Standardized execution wrapper for all modules
Config	Experiment configuration management, handles YAML configuration files
Status	Pipeline state and progress tracking, provides execution monitoring
Utils	Core utility functions and external module loading