Scaffolding for a production-quality control tree library.
Project description
controltree
controltree is a small decision-tree toolkit for tabular classification workflows, with support for manual tree-building and automated training workflows.
Package layout
src/controltree/config.py: package defaults and runtime configuration.src/controltree/schema.py: shared schema and type definitions.src/controltree/datasets.py: dataset loading helpers.src/controltree/evaluation.py: reusable metrics and model evaluation helpers.src/controltree/reporting.py: reporting and console-formatting helpers.src/controltree/builders.py: tree-building and training helpers.src/controltree/rendering.py: tree rendering and visualization support.src/controltree/workflow.py: higher-level orchestration utilities.
Installation
pip install .
For local development:
pip install -e .[dev]
Example Data
The package exposes a load_titanic() helper backed by seaborn.load_dataset("titanic") for local experimentation and demos.
Documentation
The repository is set up for Sphinx-based documentation, and the root README.md is the canonical package overview.
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