PySynthData

Generate realistic synthetic data at scale. Keep your real data private.

Create privacy-preserving datasets for AI training, testing, and demos without exposing sensitive information. Use real patterns without real risk.

30-Second Start

from pysynthdata import Synthesizer

# Learn patterns from real data
synth = Synthesizer.from_dataframe(real_df)

# Generate synthetic data (same patterns, no real data)
synthetic_df = synth.generate(rows=10000)

# Safe to share, train models, run demos
print(f"Generated {len(synthetic_df)} rows - no privacy concerns")

Why PySynthData?

The Problem:

• Real datasets contain sensitive data (PII, financial, health)
• Can't share data for AI training or testing
• Demos expose live data
• Compliance requires data anonymization

The Solution:

• Generate synthetic data with same statistical properties
• No personally identifiable information
• Scale to any size needed
• Share freely for training, testing, demos

Version History

v2.0.0 (Current)

• ✅ MCP 2.0 Support
• ✅ Integrated with 17 other projects
• ✅ 207 unified MCP tools
• ✅ Intelligent orchestration
• ✅ Production-ready (wheels only)

License

MIT

MCP 2.0 Mega-Platform | v2.0.0 | Wheels-Only Distribution