GH_CPython

Computational Design
Open Source
Bridge connecting scipy / numpy / scikit-learn to Grasshopper — high-performance scientific computing inside parametric design.
Published

January 1, 2018

GH_CPython is a bridge that brings the Python scientific stack — scipy, numpy, scikit-learn — into the Grasshopper parametric design environment, enabling high-performance numerical computing as part of an architect’s workflow.

Designed to lower the friction for designers who want to apply rigorous quantitative methods to architectural problems without abandoning their primary toolchain.