Metadata-Version: 2.4
Name: genuity
Version: 2.0.2
Summary: Genuity: A Unified Synthetic Data Library with Offline License Activation
Author: Genuity IO
License: Proprietary License
        
        Copyright (c) 2024 Genuity Team
        
        All rights reserved.
        
        This software and associated documentation files (the "Software") are proprietary 
        and confidential. Unauthorized copying, modification, distribution, or use of this 
        Software, via any medium, is strictly prohibited.
        
        The Software is licensed, not sold. Your license to use the Software is subject to 
        the terms and conditions of your purchase agreement.
        
        For licensing inquiries, please contact: cto@genuitydata.com
        
        
Project-URL: Homepage, https://github.com/genuity/genuity
Project-URL: Documentation, https://github.com/genuity/genuity
Project-URL: Repository, https://github.com/genuity/genuity
Project-URL: Issues, https://github.com/genuity/genuity/issues
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Provides-Extra: llm
Requires-Dist: transformers>=4.30.0; extra == "llm"
Provides-Extra: forest
Requires-Dist: xgboost; extra == "forest"
Provides-Extra: copula
Requires-Dist: pyvinecopulib; extra == "copula"
Provides-Extra: privacy
Requires-Dist: opacus<2.0.0,>=1.3.0; extra == "privacy"
Provides-Extra: time-series
Requires-Dist: tslearn>=0.5.0; extra == "time-series"
Requires-Dist: catch22>=0.2.0; extra == "time-series"
Requires-Dist: tsfresh>=0.19.0; extra == "time-series"
Requires-Dist: iisignature>=0.2; extra == "time-series"
Requires-Dist: torchdiffeq>=0.2.0; extra == "time-series"
Dynamic: license-file

# 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

```bash
pip install genuity
```

### Optional Extras

```bash
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

```python
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

```python
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](DOCUMENTATION.md) for the complete API reference.

## License

Proprietary. See [LICENSE](LICENSE) for details.
Contact: cto@genuitydata.com
