TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation

TNFR-Python-Engine is a Python framework for coherent-pattern analysis on graph-coupled networks. The nodal relation dEPI/dt = nu_f DeltaNFR organizes a declared evolution model; pressure, phase, capacity, support and any additional forcing require their own specifications. Version 0.0.3.7 consolidates shared numerical admission, operator contracts, cache invalidation and runtime execution provenance. Runtime step ordinals are independent of retained metrics and physical time. REMESH uses explicit cooldown bases and bounded histories. SDK and CLI reports retain unavailable diagnostic results and provenance instead of substituting evidence. The 13 registered operators, grammar U1-U6, shared integration and structural-field tetrad remain scoped engine interfaces. The release revises foundational documentation and centralizes the active research plan. A fixed finite P3 experiment compares two declared phase-pressure laws against independent form-response predictions, with pressure, integration and rounding defects separated. It distinguishes their implemented responses without selecting a physical law or proving autonomous pattern formation. Exact identities, conditional theorems, numerical observations and auxiliary models retain separate scopes. Unsupported particle and chemistry mappings, Navier-Stokes and Yang-Mills wrappers, redundant type probes and obsolete demonstrations are removed. These are intentional API removals; migration boundaries and recoverable historical sources are documented in the archive index. Routine engine/API checks are separated from retained research suites, which remain explicitly executable. See the 0.0.3.7 release, versioned source, Python package, compatibility boundaries and current documentation.