Tutorial

You can run these examples by executing the following code with your YAML config file:

exec = Executor(config=yaml_path)
exec.run()

The following scenarios guide you in choosing the right YAML configuration:

1. YAML Configuration: YAML Setup

• When you need to understand how to configure experiment parameters
• For managing and organizing complex experiment workflows
• Control all experiment settings through YAML files

2. Basic Usage: Default Synthesis

• When you only need basic data synthesis
• For simple privacy-enhanced synthetic data generation

3. Data Constraining: Data Constraining

• When you need to control synthetic data characteristics
• Includes field value rules, field combinations, and NA handling
• Ensure synthetic data meets business logic

4. Basic Usage with Evaluation: Default Synthesis and Evaluation

• When you need both synthesis and comprehensive evaluation
• Includes protection, fidelity, and utility assessments

5. Evaluation of External Solutions: External Synthesis with Default Evaluation

• When you have pre-synthesized data
• For evaluating existing privacy-enhanced solutions

6. Special Scenarios: Use Cases

• Explore different synthesis application scenarios
• Handle various practical requirements
• Provide tested workflow solutions

Simply choose the scenario that matches your needs, prepare the corresponding YAML configuration, and run the code above.