# XDFlow

XDFlow is a dimension-aware, metadata-driven ML pipeline framework for scientific data built on xarray. It keeps dimensions, coordinates, targets, groups, split policies, and transform state in the pipeline so validators and tuners can split, cache, refit, score, and align predictions by name.

Important docs for LLMs and coding agents:

- Overview: /index/
- Data contract: /concepts/data_contract/
- 5-minute core quickstart: /tutorials/quickstart/
- Spectral pipeline walkthrough: /tutorials/basic-pipeline/
- Reusable ML patterns: /tutorials/reusable-ml-patterns/
- Using XDFlow with LLMs: /guides/llm/
- Core API: /api/core/
- Composition API: /api/composition/
- Cross-validation API: /api/cv/
- Transforms API: /api/transforms/

Repository-level coding-agent instructions live in AGENTS.md.
Runnable quickstart script: examples/quickstart.py.
