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Releases: SuperInstance/constraint-theory-python

v0.1.0 — First Release: Exact Geometry for Python

27 Mar 16:51
@SuperInstance SuperInstance
v0.1.0
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v0.1.0 — First Release: Exact Geometry for Python Latest
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Python bindings for Constraint Theory — snap vectors to exact Pythagorean coordinates with zero floating-point drift, powered by Rust.

Quick Example

from constraint_theory import PythagoreanManifold, snap

# Using the class
manifold = PythagoreanManifold(density=200)
x, y, noise = manifold.snap(0.577, 0.816)
print(f"Snapped: ({x:.4f}, {y:.4f}), noise: {noise:.6f}")
# Output: Snapped: (0.6000, 0.8000), noise: 0.0236

# Using the convenience function
x, y, noise = snap(0.577, 0.816, density=200)

Key Features

  • Zero Drift — Vectors snap to exact Pythagorean triples (3/5, 4/5, etc.)
  • Blazing Fast — Rust-powered KD-tree lookups in ~100ns via PyO3 bindings
  • Batch Processing — SIMD-accelerated batch operations for thousands of vectors
  • Cross-Platform Determinism — Same results on any machine, any architecture
  • Simple API — Just snap() and snap_batch() — no configuration needed

Installation

pip install constraint-theory

Core Crate

This package provides Python bindings for the Rust implementation:
constraint-theory-core

What's Next

  • Higher-dimensional generalizations (3D Pythagorean quadruples)
  • GPU implementations (CUDA, WebGPU)
  • More language bindings
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