messydata

What problem does it solve?

MessyData enables you to generate synthetic, realistic dirty data for testing data pipelines, data quality tooling, and ML workflows without writing custom data generators.

Core Features & Use Cases

• Declarative YAML config: define datasets, distributions, and anomalies without writing procedural code.
• Date-aware generation and both CLI and Python APIs for end-to-end data generation workflows.
• Use cases include validating pipelines, stress-testing anomaly detection, and simulating real-world data quality issues.

Quick Start

Create a MessyData YAML config, then run the validate command before generating.