Synthetic data generation for ML training. Create realistic datasets for model development and testing.
Generate synthetic datasets that match your production data characteristics. Useful for testing, development, and training machine learning models without exposing real data.
from pysynthdata import Generator
# Create synthetic data matching your schema
generator = Generator(
rows=10000,
schema={
"user_id": "integer",
"email": "email",
"age": {"type": "integer", "min": 18, "max": 100},
}
)
df = generator.generate()- Generate realistic synthetic data matching your schema
- Preserve statistical properties of original data
- Support for multiple data types and distributions
- Configurable correlations between fields
- Export to CSV, Parquet, JSON
pip install pysynthdata- Testing data pipelines without real data
- ML model training and development
- Load testing databases and systems
- Privacy-preserving data sharing
- Benchmarking data processing applications
MIT License - See LICENSE