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Kuration documentation

Kuration turns sequential source data into selected, inspectable, training-ready dataset artifacts. This documentation is organized around what you are trying to accomplish rather than the package's module layout.

Start here

If you are… Read
Evaluating kuration Core concepts and product model
Building a first dataset Guided quickstart
Looking for a specific operation Pipeline guide
Integrating an internal workflow Task cookbook

Build datasets

Extend kuration

  • Building operators — package a reusable curation decision, connect bounded computation, test its contract, and distribute it as a plugin.
  • Customization and discovery — registries, descriptors, metrics, scorers, analyzers, adapters, encoders, methods, filters, containers, and presets.
  • Architecture — internal layers, execution boundaries, and design decisions.

Operate and audit

Reference

Runnable examples

The examples/ directory contains download-free demos plus bounded public-data workflows. Start with:

python examples/quickstart.py --out quickstart-out
python examples/05_custom_operators.py
python examples/06_gameplay_operator_methods.py

Every example used as a primary documentation path is exercised by CI.