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Genuity: A Unified Synthetic Data Library with Offline License Activation

Project description

Genuity v2.0.0

Enterprise-grade synthetic data generation library. 22+ generators across 5 domains: tabular, time series, financial, textual, and multi-table. Privacy-preserving with differential privacy support. Offline license activation.

Installation

pip install genuity

Optional Extras

pip install genuity[time_series]   # Time series generators
pip install genuity[copula]        # Advanced copula generators
pip install genuity[privacy]       # Differential privacy (Opacus)
pip install genuity[llm]           # LLM-based generators (GReaT)
pip install genuity[forest]        # Forest-based generators

Quick Start

import genuity

# Activate your license (one-time)
genuity.activate_license("YOUR_LICENSE_KEY")

# Generate synthetic tabular data
from genuity.tabular import create_generator

gen = create_generator("ctgan", random_seed=42)
gen.fit(your_dataframe)
result = gen.generate(n_samples=1000)

print(result.data.head())
print(result.summary())

Supported Domains

Domain Generators Entry Point
Tabular 22 (CTGAN, TVAE, TabuDiff, Copula, ARF, ...) genuity.tabular.create_generator()
Time Series 6 (TimeGAN, DGAN, DiffusionTS, ...) genuity.time_series
Financial 8 (CopulaGARCH, RegimeConditioned, ...) genuity.financial
Textual 4 (CorpusGenerator, MarkovText, ...) genuity.textual
Multi-Table 3 (GraphSchema, Federated, ...) genuity.multi_table

Evaluation

from genuity.tabular.evaluator import TabularEvaluator

evaluator = TabularEvaluator()
report = evaluator.evaluate(real_df, result.data)
print(report)
evaluator.to_html(report, output_path="report.html")

Documentation

See DOCUMENTATION.md for the complete API reference.

License

Proprietary. See LICENSE for details. Contact: cto@genuitydata.com

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