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PyQCA v0.2.0

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@t-yamsaki t-yamsaki released this 01 Jul 12:40
v0.2.0
ab914be

PyQCA v0.2.0

PyQCA v0.2.0 is the first public release candidate for the Python-native Qualitative Comparative Analysis toolkit.

Status: experimental / under active development
Please validate important empirical results against established QCA software and methodological expectations.

Highlights

  • First-class QCA engines:
    • CSQCA
    • MVQCA
    • FSQCA
    • GSQCA
  • Generalized-set QCA workflow for datasets containing crisp, multi-value, and fuzzy-set conditions.
  • Unified condition schema through ConditionSpec.
  • Truth table construction, consistency, coverage, PRI consistency, and solution summaries.
  • Pluggable minimization backends:
    • standard
    • qmc
    • set_cover
    • greedy_set_cover
    • exact_set_cover
  • Threshold-sweep analysis inspired by ThS-QCA.
  • fsQCA anchor sensitivity analysis.
  • Optional visualization and reporting utilities.
  • Markdown and formula export.
  • Reproducibility metadata and experiment logging.
  • Optional machine-learning-enhanced QCA workflow using XGBoost:
    • condition ranking
    • threshold extraction
    • crisp calibration
    • csQCA / GSQCA integration
    • Pareto model evaluation
    • CV / bootstrap stability summaries

Documentation

Documentation is available on Read the Docs:

https://pyqca.readthedocs.io/en/latest/

The stable documentation page is expected to track this release:

https://pyqca.readthedocs.io/en/stable/

Installation

After the PyPI publication workflow completes:

python -m pip install pyqca

Optional extras:

python -m pip install "pyqca[viz]"
python -m pip install "pyqca[mlqca]"
python -m pip install "pyqca[mlqca-explain]"

Methodological and License Notes

PyQCA is distributed under the MIT License.

This release includes provenance and attribution documentation:

  • LICENSE
  • THIRD_PARTY_NOTICES.md
  • PROVENANCE_AUDIT.md
  • CITATION.cff

PyQCA is methodologically informed by established QCA literature and tools, including R QCA, ThSQCA, and mlQCA, but does not bundle or execute those packages.

PyPI Publication

Publishing this GitHub Release will trigger the trusted publishing workflow for PyPI.

Expected package:

  • Project: pyqca
  • Version: 0.2.0
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