CatOpt-Query: Category-Theoretic Compositional Optimizer for Distributed Database Query Planning

Overview
- Lightweight Python prototype for expressing distributed query planning problems using category-theoretic abstractions: Objects (LocalProblem), Morphisms (SharedVariables, PlanDelta), and Functors (Adapters).
- Provides a canonical representation and a minimal solver to stitch per-shard plans into a global plan with delta-sync semantics.

Project structure
- catopt_query/protocol.py: protocol models (LocalProblem, SharedVariables, PlanDelta, CanonicalPlan)
- catopt_query/canonical.py: canonical plan representation
- catopt_query/adapters.py: adapter scaffolding (vendor -> canonical)
- catopt_query/solver.py: tiny ADMM-lite style cross-shard planner
- tests/: pytest-based tests for protocol, adapters, and solver

- DSL Primitives (new):
- PrivacyBudget, AuditLog, PolicyBlock, GraphOfContracts and extended governance hooks you can use to describe cross-shard contracts and privacy constraints.

How to run
- Run tests: pytest -q
- Build: python -m build

This repository follows the MVP goals and aims for a production-ready extension, with a focus on clear interfaces and testability.