Metadata-Version: 2.4
Name: respark
Version: 0.0.13
Summary: Generate privacy‑safe synthetic data from production Spark DataFrames
Project-URL: Source, https://github.com/dfe-analytical-services/respark
Author: Matthew Heath
License: The MIT License (MIT)
        
        Copyright © 2025 Crown Copyright (Department for Education)
        
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License-File: LICENCE
Classifier: Development Status :: 1 - Planning
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.12
Provides-Extra: dev
Requires-Dist: coverage>=7.0; extra == 'dev'
Requires-Dist: pyspark<3.6,>=3.5; extra == 'dev'
Requires-Dist: pytest-cov>=4.1; extra == 'dev'
Requires-Dist: pytest>=7; extra == 'dev'
Description-Content-Type: text/markdown


# ReSpark

**Status:** Pre-release (0.0.x)

**ReSpark** is a Python library built on **PySpark** for generating privacy-preserving synthetic data from existing Spark DataFrames or schemas. It is designed to run in **any environment where Spark is available**, whether on a local machine, a cluster, or a cloud platform.

Modern data-driven solutions require realistic datasets for development, testing, and analytics. However, using production data introduces **privacy risks** and **governance challenges**. ReSpark provides a **privacy-first approach** to synthetic data generation, preserving the structure and statistical characteristics of your original data while minimising re-identification risk.

## Vision

- **Runs Anywhere Spark Runs**: Works in any environment where Spark DataFrames are processed, from local setups to large-scale clusters.
- **Privacy-First Design**: Includes validation reporting to check for residual sensitive information or re-identification risk.
- **Relational Integrity**: Maintains join consistency with appropriate handling of sensitive and non-sensitive fields.

## Installation

```bash
pip install respark
```

This package requires `pyspark` (Apache-2.0)

## Licence

© Crown Copyright 2025 Department for Education  
Licensed under the MIT Licence.

## Acknowledgements

Built on Apache Spark / PySpark (Apache License 2.0).
