Public APIs

API reference overview

This page routes developers to the package API reference and the most common generation workflows.

Great Generator creates synthetic data. It does not anonymize, mask, de-identify, or transform production records.

Getting started API reference GitHub

Common imports

Most users start with schema generation, DDL parsing, relational generation, or domain generation.

from great_generator import generate_from_schema, parse_ddl, generate_relational
from great_generator import generate_domain, generate_cdc

Full reference

The detailed API reference lives in the repository documentation and should be updated when public APIs change.

Related documentation

Keep exploring

Getting started with Great GeneratorInstall Great Generator and create synthetic non-production data from schemas, SQL DDL, and related-table definitions for development and testing. Generate synthetic data from schemasCreate synthetic test data from schema strings, dictionaries, Pandas DataFrames, and Spark schemas using semantic field detection. SQL DDL synthetic data workflowsParse SQL CREATE TABLE statements into schema contracts and generate synthetic data for ANSI, Spark, and Databricks-style table definitions. Relational synthetic dataGenerate related synthetic tables with primary-key and foreign-key behavior for joins, warehouse models, tests, demos, and analytics examples. GitHub repositorySource code, issues, releases, and project history. PyPI packageInstall Great Generator from Python Package Index.